Preface |
NIPS Committees |
Reviewers |
Algorithms and Architectures / Part I: |
Efficient Multiscale Sampling from Products of Gaussian Mixtures / Alexander T. Ihler ; Erik B. Sudderth ; William T. Freeman ; Alan S. Willsky |
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles / Mark Girolami ; Ata Kaban |
Hierarchical Topic Models and the Nested Chinese Restaurant Process / David Blei ; Thomas L. Griffiths ; Michael I. Jordan ; Joshua B. Tenenbaum |
Max-Margin Markov Networks / Ben Taskar ; Carlos Guestrin ; Daphne Koller |
Invariant Pattern Recognition by Semi-Definite Programming Machines / Thore Graepel ; Ralf Herbrich |
Learning a Distance Metric from Relative Comparisons / Matthew Schultz ; Thorsten Joachims |
1-norm Support Vector Machines / Ji Zhu ; Saharon Rosset ; Trevor Hastie ; Rob Tibshirani |
Image Reconstruction by Linear Programming / Koji Tsuda ; Gunnar Ratsch |
Multiple-Instance Learning via Disjunctive Programming Boosting / Stuart Andrews ; Thomas Hofmann |
Convex Methods for Transduction / Tijl De Bie ; Nello Cristianini |
Kernel Dimensionality Reduction for Supervised Learning / Kenji Fukumizu ; Francis R. Bach |
Clustering with the Connectivity Kernel / Bernd Fischer ; Volker Roth ; Joachim M. Buhmann |
Efficient and Robust Feature Extraction by Maximum Margin Criterion / Haifeng Li ; Tao Jiang ; Keshu Zhang |
Sparse Greedy Minimax Probability Machine Classification / Thomas Strohmann ; Andrei Belitski ; Greg Grudic ; Dennis DeCoste |
Sequential Bayesian Kernel Regression / Jaco Vermaak ; Simon J. Godsill ; Arnaud Doucet |
Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms / Claudio Gentile |
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction / Liva Ralaivola ; Florence d'Alche-Buc |
Extreme Components Analysis / Max Welling ; Felix Agakov ; Christopher K. I. Williams |
Linear Dependent Dimensionality Reduction / Nathan Srebro ; Tommi S. Jaakkola |
Locality Preserving Projections / Xiaofei He ; Partha Niyogi |
Optimal Manifold Representation of Data: An Information Theoretic Approach / Denis V. Chigirev ; William Bialek |
Ranking on Data Manifolds / Dengyong Zhou ; Jason Weston ; Arthur Gretton ; Olivier Bousquet ; Bernhard Scholkopf |
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering / Yoshua Bengio ; Jean-Francois Paiement ; Pascal Vincent ; Olivier Delalleau ; Nicolas Le Roux ; Marie Ouimet |
Pairwise Clustering and Graphical Models / Noam Shental ; Assaf Zomet ; Tomer Hertz ; Yair Weiss |
Tree-structured Approximations by Expectation Propagation / Thomas Minka ; Yuan Qi |
The IM Algorithm: A Variational Approach to Information Maximization / David Barber |
Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian-Vector Multiply / Eiji Mizutani ; James W. Demmel |
Large Scale Online Learning / Leon Bottou ; Yann Le Cun |
Online Classification on a Budget / Koby Crammer ; Jaz Kandola ; Yoram Singer |
Online Learning via Global Feedback for Phrase Recognition / Xavier Carreras ; Lluis Marquez |
Sparse Representation and Its Applications in Blind Source Separation / Yuanqing Li ; Andrzej Cichocki ; Shun-ichi Amari ; Sergei Shishkin ; Jianting Cao ; Fanji Gu |
Perspectives on Sparse Bayesian Learning / David Wipf ; Jason Palmer ; Bhaskar Rao |
Semi-Supervised Learning with Trees / Charles Kemp ; Sean Stromsten |
Efficient Exact k-NN and Nonparametric Classification in High Dimensions / Ting Liu ; Andrew W. Moore ; Alexander Gray |
Nonstationary Covariance Functions for Gaussian Process Regression / Christopher J. Paciorek ; Mark J. Schervish |
Learning the k in k-means / Greg Hamerly ; Charles Elkan |
Finding the M Most Probable Configurations in Arbitrary Graphical Models / Chen Yanover |
Non-linear CCA and PCA by Alignment of Local Models / Jakob J. Verbeek ; Sam T. Roweis ; Nikos Vlassis |
Learning Spectral Clustering |
AUC Optimization vs. Error Rate Minimization / Corinna Cortes ; Mehryar Mohri |
Learning with Local and Global Consistency / Thomas Navin Lal |
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data / Neil D. Lawrence |
Warped Gaussian Processes / Edward Snelson ; Carl Edward Rasmussen ; Zoubin Ghahramani |
Can We Learn to Beat the Best Stock / Allan Borodin ; Ran El-Yaniv ; Vincent Gogan |
Approximate Expectation Maximization / Tom Heskes ; Onno Zoeter ; Wim Wiegerinck |
Linear Response for Approximate Inference / Yee Whye Teh |
Semidefinite Relaxations for Approximate Inference on Graphs with Cycles / Martin Wainwright |
Approximability of Probability Distributions / Alina Beygelzimer ; Irina Rish |
Denoising and Untangling Graphs Using Degree Priors / Quaid D. Morris ; Brendan J. Frey |
On the Concentration of Expectation and Approximate Inference in Layered Networks / XuanLong Nguyen |
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models / Radford M. Neal ; Matthew J. Beal |
Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis / Pedro F. Felzenswalb ; Daniel P. Huttenlocher ; Jon M. Kleinberg |
Wormholes Improve Contrastive Divergence / Geoffrey Hinton ; Andriy Mnih |
Sample Propagation / Mark A. Paskin |
Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data / Amos J Storkey |
Laplace Propagation / Alexander Smola ; Vishy Vishwanathan ; Eleazar Eskin |
Learning to Find Pre-Images / Goekhan H. Bakir |
Semi-Definite Programming by Perceptron Learning / Andriy Kharechko ; John Shawe-Taylor |
Computing Gaussian Mixture Models with EM Using Equivalence Constraints / Aharon Bar-Hillel ; Daphna Weinshall |
Feature Selection in Clustering Problems / Tilman Lange |
An Iterative Improvement Procedure for Hierarchical Clustering / David Kauchak ; Sanjoy Dasgupta |
Identifying Structure across Pre-partitioned Data / Zvika Marx ; Ido Dagan ; Eli Shamir |
Log-Linear Models for Label Ranking / Ofer Dekel ; Christopher Manning |
Minimax Embeddings / Matthew Brand |
No Unbiased Estimator of the Variance of K-Fold Cross-Validation / Yves Grandvalet |
Bias-Corrected Bootstrap and Model Uncertainty / Harald Steck |
Probability Estimates for Multi-Class Classification by Pairwise Coupling / Ting-Fan Wu ; Chih-Jen Lin ; Ruby C. Weng |
Necessary Intransitive Likelihood-Ratio Classifiers / Gang Ji ; Jeff Bilmes |
Classification with Hybrid Generative/Discriminative Models / Rajat Raina ; Yirong Shen ; Andrew Y. Ng ; Andrew McCallum |
A Model for Learning the Semantics of Pictures / Victor Lavrenko ; R. Manmatha ; Jiwoon Jeon |
Algorithms for Interdependent Security Games / Michael Kearns ; Luis Ortiz |
Applications / Part II: |
Fast Embedding of Sparse Similarity Graphs / John C. Platt |
GPPS: A Gaussian Process Positioning System for Cellular Networks / Anton Schwaighofer ; Marian Grigoras ; Volker Tresp ; Clemens Hoffmann |
An Autonomous Robotic System for Mapping Abandoned Mines / David Ferguson ; Aaron Morris ; Dirk Hahnel ; Christopher Baker ; Zachary Omohundro ; Carlos Reverte ; Scott Thayer ; Charles Whittaker ; William Whittaker ; Wolfram Burgard ; Sebastian Thrun |
Semi-supervised Protein Classification Using Cluster Kernels / Christina Leslie ; Andre Elisseeff ; William S. Noble |
Statistical Debugging of Sampled Programs / Alice X. Zheng ; Ben Liblit ; Alex Aiken |
Markov Models for Automated ECG Interval Analysis / Nicholas P. Hughes ; Lionel Tarassenko ; Stephen J. Roberts |
Parameterized Novelty Detectors for Environmental Sensor Monitoring / Cynthia Archer ; Todd K. Leen ; Antonio Baptista |
Modeling User Rating Profiles For Collaborative Filtering / Benjamin Marlin |
Application of SVMs for Colour Classification and Collision Detection with AIBO Robots / Michael J. Quinlan ; Stephan K. Chalup ; Richard H. Middleton |
Kernels for Structured Natural Language Data / Jun Suzuki ; Yutaka Sasaki ; Eisaku Maeda |
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters / Daniel B. Neill |
Link Prediction in Relational Data / Ming-Fai Wong ; Pieter Abbeel |
Unsupervised Color Decomposition Of Histologically Stained Tissue Samples / Andrew Rabinovich ; Sameer Agarwal ; Casey Laris ; Jeffrey H. Price ; Serge J. Belongie |
ICA-based Clustering of Genes from Microarray Expression Data / Su-In Lee ; Serafim Batzoglou |
Gene Expression Clustering with Functional Mixture Models / Darya Chudova ; Christopher Hart ; Eric Mjolsness ; Padhraic Smyth |
Brain Imaging / Part III: |
Reconstructing MEG Sources with Unknown Correlations / Maneesh Sahani ; Srikantan S. Nagarajan |
Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales / Saori C. Tanaka ; Kenji Doya ; Go Okada ; Kazutaka Ueda ; Yasumasa Okamoto ; Shigeto Yamawaki |
Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects / Xuerui Wang ; Rebecca Hutchinson ; Tom M. Mitchell |
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression / Roland Vollgraf ; Michael Scholz ; Ian A. Meinertzhangen ; Klaus Obermayer |
Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interface / Yu Zhou ; Steven G. Mason ; Gary E. Birch |
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class / Guido Dornhege ; Benjamin Blankertz ; Gabriel Curio ; Klaus-Robert Muller |
Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron / Sung C. Jun ; Barak A. Pearlmutter |
Control and Reinforcement Learning / Part IV: |
Gaussian Processes in Reinforcement Learning / Malte Kuss |
Applying Metric-Trees to Belief-Point POMDPs / Joelle Pineau ; Geoffrey J. Gordon |
ARA*: Anytime A* with Provable Bounds on Sub-Optimality / Maxim Likhachev |
Approximate Planning in POMDPs with Macro-Actions / Georgios Theocharous ; Leslie Pack Kaelbling |
Envelope-based Planning in Relational MDPs / Natalia H. Gardiol |
An MDP-Based Approach to Online Mechanism Design / David C. Parkes ; Satinder Singh |
Autonomous Helicopter Flight via Reinforcement Learning / H. Jin Kim ; Shankar Sastry |
All learning is Local: Multi-agent Learning in Global Reward Games / Yu-Han Chang ; Tracey Ho |
How to Combine Expert (and Novice) Advice when Actions Impact the Environment? / Daniela Pucci de Farias ; Nimrod Megiddo |
Bounded Finite State Controllers / Pascal Poupart ; Craig Boutilier |
Policy Search by Dynamic Programming / J. Andrew Bagnell ; Sham Kakade ; Jeff Schneider |
Robustness in Markov Decision Problems with Uncertain Transition Matrices / Arnab Nilim ; Laurent El Ghaoui |
Approximate Policy Iteration with a Policy Language Bias / Alan Fern ; Sungwook Yoon ; Robert Givan |
A Nonlinear Predictive State Representation / Matthew R. Rudary |
Learning Near-Pareto-Optimal Conventions in Polynomial Time / XiaoFeng Wang ; Tuomas Sandholm |
Extending Q-Learning to General Adaptive Multi-Agent Systems / Gerald Tesauro |
Auction Mechanism Design for Multi-Robot Coordination / Curt Bererton |
Distributed Optimization in Adaptive Networks / Ciamac C. Moallemi ; Benjamin Van Roy |
Linear Program Approximations for Factored Continuous-State Markov Decision Processes / Milos Hauskrecht ; Branislav Kveton |
Cognitive Science and Artificial Intelligence / Part V: |
Insights from Machine Learning Applied to Human Visual Classification / Arnulf B. A. Graf ; Felix A. Wichmann |
Sensory Modality Segregation / Virginia R. de Sa |
Reasoning about Time and Knowledge in Neural Symbolic Learning Systems / Artur S. d'Avila Garcez ; Luis C. Lamb |
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System / Marc Toussaint |
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science / Woojae Kim ; Daniel J. Navarro ; Mark A. Pitt ; In Jae Myung |
Perception of the Structure of the Physical World Using Unknown Multimodal Sensors and Effectors / D. Philipona ; J.K. O'Regan ; J.-P. Nadal ; Olivier Coenen |
From Algorithmic to Subjective Randomness |
Unsupervised Context Sensitive Language Acquisition from a Large Corpus / Zach Solan ; David Horn ; Eytan Ruppin ; Shimon Edelman |
A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot Experiments / Yuuya Sugita ; Jun Tani |
Model Uncertainty in Classical Conditioning / Aaron C. Courville ; Nathaniel Daw ; David S. Touretzky |
Emerging Technologies / Part VI: |
A Low-Power Analog VLSI Visual Collision Detector / Reid R. Harrison |
A Recurrent Model of Orientation Maps with Simple and Complex Cells / Paul Merolla ; Kwabena Boahen |
A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural Systems / Rock Z. Shi ; Timothy Horiuchi |
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons / Hsin Chen ; Patrice Fleury ; Alan F. Murray |
Training a Quantum Neural Network / Bob Ricks ; Dan Ventura |
Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses / Adria Bofill-i-Petit |
A Mixed-Signal VLSI for Real-Time Generation of Edge-Based Image Vectors / Masakazu Yagi ; Hideo Yamasaki ; Tadashi Shibata |
Entrainment of Silicon Central Pattern Generators for Legged Locomotory Control / Francesco Tenore ; Ralph Etienne-Cummings ; M. Anthony Lewis |
A Neuromorphic Multi-chip Model of a Disparity Selective Complex Cell / Eric K. C. Tsang ; Bertram E. Shi |
Learning Theory / Part VII: |
Invited Talk: Message passing in random satisfiability problems / Marc Mezard |
Sparseness of Support Vector Machines--Some Asymptotically Sharp Bounds / Ingo Steinwart |
An Infinity-sample Theory for Multi-category Large Margin Classification / Tong Zhang |
Error Bounds for Transductive Learning via Compression and Clustering / Philip Derbeko ; Ron Meir |
Online Learning of Non-stationary Sequences / Claire Monteleoni |
On the Dynamics of Boosting / Cynthia Rudin ; Ingrid Daubechies ; Robert Schapire |
Boosting versus Covering / Kohei Hatano ; Manfred K. Warmuth |
Near-Minimax Optimal Classification with Dyadic Classification Trees / Clayton Scott ; Robert Nowak |
PAC-Bayesian Generic Chaining / Jean-Yves Audibert |
Self-calibrating Probability Forecasting / Vladimir Vovk ; Glenn Shafer ; Ilia Nouretdinov |
When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? / David Donoho ; Victoria Stodden |
Learning Bounds for a Generalized Family of Bayesian Posterior Distributions |
Variational Linear Response / Manfred Opper ; Ole Winther |
Geometric Clustering Using the Information Bottleneck Method / Susanne Still |
Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates / Peter L. Bartlett ; Jon D. McAuliffe |
Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA / David Hoyle ; Magnus Rattray |
Approximate Analytical Bootstrap Averages for Support Vector Classifiers / Dorthe Malzahn |
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks / Justin Werfel ; Xiaohui Xie ; H. Sebastian Seung |
Ambiguous Model Learning Made Unambiguous with I/f Priors / Gurinder S. Atwal |
Information Bottleneck for Gaussian Variables / Gal Chechik ; Amir Globerson ; Naftali Tishby |
Measure Based Regularization / Olivier Chapelle ; Matthias Hein |
Online Passive-Aggressive Algorithms / Shai Shalev-Shwartz |
Margin Maximizing Loss Functions |
Neuroscience / Part VIII: |
The Doubly Balanced Network of Spiking Neurons: A Memory Model with High Capacity / Yuval Aviel ; Moshe Abeles |
Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons / Thomas Natschlager ; Wolfgang Maass |
The Diffusion-Limited Biochemical Signal-Relay Channel / Peter J. Thomas ; Donald J. Spencer ; Sierra K. Hampton ; Peter Park ; Joseph P. Zurkus |
Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory / Aaron J. Gruber ; Peter Dayan ; Boris S. Gutkin ; Sara A. Solla |
Circuit Optimization Predicts Dynamic Network for Chemosensory Orientation in the Nematode C. elegans / Nathan A. Dunn ; John S. Conery ; Shawn R. Lockery |
A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning |
Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron? / Yoichi Miyawaki ; Masato Okada |
Plasticity Kernels and Temporal Statistics / Michael Hausser |
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model / Jonathan Pillow ; Liam Paninski ; Eero P. Simoncelli |
Design of Experiments via Information Theory |
Probabilistic Inference in Human Sensorimotor Processing / Konrad P. Kording ; Daniel Wolpert |
Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter / Kazuyuki Samejima ; Yasumasa Ueda ; Minoru Kimura |
Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic Biophysics / Bernd Porr ; Ausra Saudargiene ; Florentin Worgotter |
A Probabilistic Model of Auditory Space Representation in the Barn Owl / Brian J. Fischer ; Charles H. Anderson |
Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels / Ryan Kelly ; Tai Sing Lee |
Prediction on Spike Data Using Kernel Algorithms / Jan Eichhorn ; Andreas Tolias ; Alexander Zien ; Nikos Logothetis |
Speech and Signal Processing / Part IX: |
Phonetic Speaker Recognition with Support Vector Machines / William M. Campbell ; Joseph P. Campbell ; Douglas A. Reynolds ; Douglas A. Jones ; Timothy R. Leek |
A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications / Pedro J. Moreno ; Purdy P. Ho ; Nuno Vasconcelos |
Probabilistic Inference of Speech Signals from Phaseless Spectrograms / Kannan Achan |
Eigenvoice Speaker Adaptation via Composite Kernel PCA / James T. Kwok ; Brian Mak ; Simon Ho |
Predicting Speech Intelligibility from a Population of Neurons / Jeff Bondy ; Ian Bruce ; Suzanna Becker ; Simon Haykin |
One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals / Tomohiro Nakatani ; Masato Miyoshi ; Keisuke Kinoshita |
A Classification-based Cocktail-party Processor / Nicoleta Roman ; DeLiang Wang ; Guy J. Brown |
Visual Processing / Part X: |
Local Phase Coherence and the Perception of Blur / Zhou Wang |
Nonlinear Processing in LGN Neurons / Vincent Bonin ; Valerio Mante ; Matteo Carandini |
A Functional Architecture for Motion Pattern Processing in MSTd / Scott A. Beardsley ; Lucia M. Vaina |
Human and Ideal Observers for Detecting Image Curves / A.L. Yuille ; Fang Fang ; Paul Schrater ; Daniel Kersten |
Eye Movements for Reward Maximization / Nathan Sprague ; Dana Ballard |
Eye Micro-movements Improve Stimulus Detection Beyond the Nyquist Limit in the Peripheral Retina / Matthias H. Hennig |
Bounded Invariance and the Formation of Place Fields / Reto Wyss ; Paul F. M. J. Verschure |
Discriminating Deformable Shape Classes / Salvador Ruiz-Correa ; Linda G. Shapiro ; Marina Meila ; Gabriel Berson |
Graphical Model For Recognizing Scenes and Objects / Kevin Murphy ; Antonio Torralba |
Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence / Amit Gruber |
Mutual Boosting for Contextual Inference / Michael Fink ; Pietro Perona |
Learning a Rare Event Detection Cascade by Direct Feature Selection / Jianxin Wu ; James M. Rehg ; Matthew D. Mullin |
Discriminative Fields for Modeling Spatial Dependencies in Natural Images / Sanjiv Kumar ; Martial Hebert |
Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation / Leonid Sigal ; Michael Isard ; Benjamin H. Sigelman ; Michael J. Black |
Automatic Annotation of Everyday Movements / Deva Ramanan ; David A. Forsyth |
Learning Non-Rigid 3D Shape from 2D Motion / Lorenzo Torresani ; Aaron Hertzmann ; Christoph Bregler |
Towards Social Robots: Automatic Evaluation of Human-Robot Interaction by Face Detection and Expression Classification / Gwen Littlewort ; Marian S. Bartlett ; Ian Fasel ; Joel Chenu ; Takayuki Kanda ; Hiroshi Ishiguro ; Javier R. Movellan |
Salient Boundary Detection using Ratio Contour / Song Wang ; Toshiro Kubota ; Jeffrey Mark Siskind |
A Computational Geometric Approach to Shape Analysis in Images / Anuj Srivastava ; Xiuwen Liu ; Washington Mio ; Eric Klassen |
A Sampled Texture Prior for Image Super-Resolution / Lyndsey C. Pickup ; Andrew Zisserman |
Bayesian Color Constancy with Non-Gaussian Models / Charles Rosenberg ; Alok Ladsariya |
An Improved Scheme for Detection and Labelling in Johansson Displays / Claudio Fanti ; Marzia Polito |
Index of Authors |
Keyword Index |
Cognitive Science |
Text-Based Information Retrieval Using Exponentiated Gradient Descent |
Why did TD-Gammon Work? |
Neural Models for Part-Whole Hierarchies |
Temporal Low-Order Statistics of Natural Sounds |
Reconstructing Stimulus Velocity from Neuronal Responses in Area MT |
3D Object Recognition: A Model of View-Tuned Neurons |
A Hierarchical Model of Visual Rivalry |
Neural Network Models of Chemotaxis in the Nematode Caenorhabditis Elegans |
Extraction of Temporal Features in the Electrosensory System of Weakly Electric Fish |
A Neural Model of Visual Contour Integration |
Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings |
Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation |
Orientation Contrast Sensitivity from Long-range Interactions in Visual Cortex |
Statistically Efficient Estimations Using Cortical Lateral Connections |
An Architectural Mechanism for Direction-tuned Cortical Simple Cells: The Role of Mutual Inhibition |
Cholinergic Modulation Preserves Spike Timing Under Physiologically Realistic Fluctuating Input |
A Model of Recurrent Interactions in Primary Visual Cortex |
Theory |
Neural Learning in Structured Parameter Spaces Natural |
Riemannian Gradient |
For Valid Generalization, the Size of the Weights is More Important than the Size of the Network |
Dynamics of Training |
Multilayer Neural Networks: One or Two Hidden Layers? |
Support Vector Regression Machines |
Size of Multilayer Networks for Exact Learning: Analytic Approach |
The Effect of Correlated Input Data on the Dynamics of Learning |
Practical Confidence and Prediction Intervals |
Statistical Mechanics of the Mixture of Experts |
MLP Can Probably Generalize Much Better than VC-bounds Indicate |
Radial Basis Function Networks and Complexity Regularization in Function Learning |
An Apobayesian Relative of Winnow |
Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons |
On the Effect of Analog Noise in Discrete-Time Analog Computations |
A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks |
Removing Noise in On-Line Search using Adaptive Batch Sizes |
Are Hopfield Networks Faster than Conventional Computers? |
Hebb Learning of Features based on their Information Content |
The Generalisation Cost of RAMnets |
Learning with Noise and Regularizers in Multilayer Neural Networks |
A Variational Principle for Model-based Morphing |
Online Learning from Finite Training Sets: An Analytical Case Study |
Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing |
The Learning Dynamics of a Universal Approximator |
Computing with Infinite Networks |
Microscopic Equations in Rough Energy Landscape for Neural Networks |
Time Series Prediction using Mixtures of Experts |
Algorithms and Architecture |
Genetic Algorithms and Explicit Search Statistics |
Consistent Classification, Firm and Soft |
Bayesian Model Comparison by Monte Carlo Chaining |
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo |
Regression with Input-Dependent Noise: A Bayesian Treatment |
GTM: A Principled Alternative to the Self-Organizing Map |
The Condensation Algorithm Conditional Density Propagation and Applications to Visual Tracking |
Neural Clustering via Concave Minimization |
Improving the Accuracy and Speed of Support Vector Machines |
Estimating Equivalent Kernels for Neural Networks: A Data Perturbation Approach |
Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs |
Self-Organizing and Adaptive Algorithms for Generalized Eigen-Decomposition |
Representation and Induction of Finite State Machines using Time-Delay Neural Networks |
Solutions to the XOR Problem |
Minimizing Statistical Bias with Queries |
MIMIC: Finding Optima by Estimating Probability Densities |
On a Modification to the Mean Field EM Algorithm in Factorial Learning |
Softening Discrete Relaxation |
Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling |
Continuous Sigmoidal Belief Networks Trained using Slice Sampling |
Adaptively Growing Hierarchical Mixtures of Experts |
Balancing Between Bagging and Bumping |
LSTM can Solve Hard Long Time Lag Problems |
One-unit Learning Rules for Independent Component Analysis |
Recursive Algorithms for Approximating Probabilities in Graphical Models |
Combinations of Weak Classifiers |
Hidden Markov Decision Trees |
Unification of Information Maximization and Minimization |
Unsupervised Learning by Convex and Conic Coding |
ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers |
Bayesian Unsupervised Learning of Higher Order Structure |
Source Separation and Density Estimation by Faithful Equivariant SOM |
NeuroScale: Novel Topographic Feature Extraction using RBF Networks |
Decomposition, Ordered Classes and Incomplete Examples in Classification |
Triangulation by Continuous Embedding |
Time-Delay Neural Combining Neural Network Regression Estimates with Regularized Linear Weights |
A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data |
Learning Bayesian Belief Networks with Neural Network Estimators |
Smoothing Regularizers for Projective Basis Function Networks |
Competition Among Networks Improves Committee Performance |
Adaptive On-line Learning in Changing Environments |
Using Curvature Information for Fast Stochastic Search |
Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA |
A Convergence Proof for the Soft assign Quadratic Assignment Algorithm |
Second-order Learning Algorithm with Squared Penalty Term |
Monotonicity Hints |
Training Algorithms for Hidden Markov Models using Entropy Based Distance Models |
Clustering Sequences with Hidden Markov Models |
Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm |
Separating Style and Content |
Early Brain Damage |
Implementation |
VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer |
A Spike Based Learning Neuron in Analog VLSI |
An Analog Implementation of the Constant Average Statistics Constraint For Sensor Calibration |
Analog VLSI Circuits for Attention-Based, Visual Tracking |
Dynamically Adaptable CMOS Winner-Take-AII Neural Network |
An Adaptive WTA using Floating Gate Technology |
A Micropower Analog VLSI HMM State Decoder for Wordspotting |
Bangs, Clicks, Snaps, Thuds and Whacks: An Architecture for Acoustic Transient Processing |
A Silicon Model of Amplitude Modulation Detection in the Auditory Brainstem |
Speech |
Handwriting and Signal Processing Dynamic Features for Visual Speechreading: A Systematic Comparison |
Blind Separation of Delayed and Convolved Sources |
A Constructive RBF Network for Writer Adaptation |
A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks |
Neural Network Modeling of Speech and Music Signals |
A Constructive Learning Algorithm for Discriminant Tangent Models |
Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation |
Ensemble Methods for Phoneme Classification |
Effective Training of a Neural Network Character Classifier for Word Recognition |
Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks |
Learning Temporally Persistent Hierarchical Representations |
Edges are the "Independent Components" of Natural Scenes |
Compositionality, MDL Priors, and Object Recognition |
Learning Appearance Based Models: Mixtures of Second Moment Experts |
Spatial Decorrelation in Orientation Tuned Cortical Cells |
Spatiotemporal Coupling and Scaling of Natural Images and Human Visual Sensitivities |
Selective Integration: A Model for Disparity Estimation |
ARTEX: A Self-organizing Architecture for Classifying Image Regions |
Contour Organisation with the EM Algorithm |
Visual Cortex Circuitry and Orientation Tuning |
Representing Face Images for Emotion Classification |
Rapid Visual Processing using Spike Asynchrony |
Interpreting Images by Propagating Bayesian Beliefs |
Salient Contour Extraction by Temporal Binding in a Cortically-based Network |
An Orientation Selective Neural Network for Pattern Identification in Particle Detectors |
Adaptive Access Control Applied to Ethernet Data |
Predicting Lifetimes in Dynamically Allocated Memory |
Multi-Task Learning for Stock Selection |
The Neurothermostat: Predictive Optimal Control of Residential Heating Systems |
Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches |
A Comparison between Neural Networks and other Statistical Techniques for Modeling the Relationship between Tobacco and Alcohol and Cancer |
Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems |
Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks |
Interpolating Earth-science Data using RBF Networks and Mixtures of Experts |
Multi-effect Decompositions for Financial Data Modeling |
Control, Navigation and Planning |
Multidimensional Triangulation and Interpolation for Reinforcement Learning |
Efficient Nonlinear Control with Actor-Tutor Architecture |
Local Bandit Approximation for Optimal Learning Problems |
Reinforcement Learning for Mixed Open-loop and Closed-loop Control |
Multi-Grid Methods for Reinforcement Learning in Controlled Diffusion Processes |
Learning from Demonstration |
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning |
Analytical Mean Squared Error Curves in Temporal Difference Learning |
Learning Decision Theoretic Utilities through Reinforcement Learning |
On-line Policy Improvement using Monte-Carlo Search |
Analysis of Temporal-Difference Learning with Function Approximation |
Approximate Solutions to Optimal Stopping Problems |
Contributors |
Direction Selectivity in Primary Visual Cortex Using Massive Intracortical Connections |
On the Computational Utility of Consciousness |
Catastrophic Interference in Human Motor Learning |
Grammar Learning by a Self-Organizing Network |
Patterns of Damage in Neural Networks: The Effects of Lesion Area, Shape and Number |
Forward Dynamic Models in Human Motor Control Psychophysical Evidence |
A Solvable Connectionist Model of Immediate Recall of Ordered Lists |
A Model for Chemosensory Reception |
The Electronic Transformation: A Tool for Relating Neuronal Form to Function |
A Model of the Hippocampus Combining Self-Organization and Associative Memory Function |
A Model of Biological Neuron as a Temporal Neural Network |
A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex |
A Novel Reinforcement Model of Birdsong Vocalization Learning |
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex |
Anatomical Origin and Computational Role of Diversity in the Response Properties of Cortical Neurons |
Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl |
Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure |
A Computational Model of Prefrontal Cortex Function |
A Neural Model of Delusions and Hallucinations in Schizophrenia |
Spatial Representations in the Parietal Cortex May Use Basis Functions |
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex |
A Model of the Neural Basis of the Rat's Sense Of Direction |
Learning Theory and Dynamics |
On the Computational Complexity of Networks of Spiking Neurons |
H∞ |
Optimal Training Algorithms and Their Relation to Back Propagation |
Synchrony and Desynchrony in Neural Oscillator Networks |
Learning in Large Linear Perceptrons and Why the Thermodynamic Limit Is Relevant to the Real World |
Generalisation in Feedforward Networks |
From Data Distributions to Regularization in Invariant Learning |
Neural Network Ensembles, Cross Validation, and Active Learning |
Limits on Learning Machine Accuracy Imposed by Data Quality |
Higher Order Statistical Decorrelation without Information Loss |
Hyperparameters, Evidence and Generalisation for an Unrealisable Rule |
Temporal Dynamics of Generalization in Neural Networks |
Stochastic Dynamics of Three-State Neural Networks |
Learning Stochastic Perceptrons under K-Blocking Distributions |
Learning from Queries for Maximum Information Gain in Imperfectly Learnable Problems |
Bias, Variance and the Combination of Least Squares Estimators |
On-Line Learning of Dichotomies |
Dynamic Modelling of Chaotic Time Series with Neural Networks |
A Rigorous Analysis of Linsker-Type Hebbian Learning |
Sample Size Requirements for Feedforward Neural Networks |
Asymptotics of Gradient-Based Neural Network Training Algorithms |
Reinforcement Learning |
Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems |
Advantage Updating Applied to a Differential Game |
Reinforcement Learning with Soft State Aggregation |
Generalization in Reinforcement Learning: Safely Approximating the Value Function |
Instance-Based State Identification for Reinforcement Learning |
Finding Structure in Reinforcement Learning |
Reinforcement Learning Methods for Continuous-Time Markov Decision Problems |
An Actor/Critic Algorithm that Is Equivalent to Q-Learning |
Financial Applications of Learning from Hints (Invited Paper) |
Combining Estimators Using Non-Constant Weighting Functions |
An Input Output HMM Architecture |
Boltzmann Chains and Hidden Markov Models |
Bayesian Query Construction for Neural Network Models |
Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results |
Multidimensional Scaling and Data Clustering |
A Non-Linear Information Maximisation Algorithm that Performs Blind Separation |
Plasticity-Mediated Competitive Learning |
Phase-Space Learning |
Learning Local Error Bars for Nonlinear Regression |
Dynamic Cell Structures |
Extracting Rules from Artificial Neural Networks with Distributed Representations |
Capacity and Information Efficiency of a Brain-Like Associative Net |
Boosting the Performance of RBF Networks with Dynamic Decay Adjustment |
Simplifying Neural Nets BY Discovering Flat Minima |
Learning with Product Units |
Deterministic Annealing Variant of the EM Algorithm |
Diffusion of Credit in Markovian Models |
Factorial Learning by Clustering Features |
Interior Point Implementations of Alternating Minimization Training |
SARDNET: A Self-Organizing Feature Map for Sequences |
Convergence Properties of the K-Means Algorithms |
Active Learning for Function Approximation |
Analysis of Unstandardized Contributions in Cross Connected Networks |
Template-Based Algorithms for Connectionist Rule Extraction |
Factorial Learning and the EM Algorithm |
A Growing Neural Gas Network Learns Topologies |
An Alternative Model for Mixtures of Experts |
Estimating Conditional Probability Densities for Periodic Variables |
Effects of Noise on Convergence and Generalization in Recurrent Networks |
Learning Many Related Tasks at the Same Time with Backpropagation |
A Rapid Graph-Based Method for Arbitrary Transformation-Invariant Pattern Classification |
Recurrent Networks: Second Order Properties and Pruning |
Classifying with Gaussian Mixtures and Clusters |
Efficient Methods for Dealing with Missing Data in Supervised Learning |
An Experimental Comparison of Recurrent Neural Networks |
Active Learning with Statistical Models |
Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures |
Direct Multi-Step Time Series Prediction Using TD(λ) |
Implementations |
ICEG Morphology Classification Using an Analogue VLSI Neural Network |
A Silicon Axon |
The NI1000: High Speed Parallel VLSI For Implementing Multilayer Perceptrons |
A Real Time Clustering CMOS Neural Engine |
Pulsestream Synapses with Non-Volatile Analogue Amorphous-Silicon Memories |
A Lagrangian Formulation for Optical Backpropagation Training in Kerr-Type Optical Networks |
A Charge-Based CMOS Parallel Analog Vector Quantizer |
An Auditory Localization and Coordinate Transform Chip |
An Analog Neural Network Inspired by Fractal Block Coding |
A Study of Parallel Perturbative Gradient Descent |
Implementation of Neural Hardware with the Neural VLSI of Uran in Applications with Reduced Representations |
Single Transistor Learning Synapses |
Pattern Playback in the '90S (Invited Paper) |
Non-Linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts |
GLOVE-TALKII: Mapping Hand Gestures to Speech Using Neural Networks |
Visual Speech Recognition with Stochastic Networks |
Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition |
Connectionist Speaker Normalization with Generalized Resource Allocating Networks |
Using Voice Transformations to Create Additional Training Talkers for Word Spotting |
A Comparison of Discrete-Time Operator Models for Nonlinear System Identification |
Learning Saccadic Eye Movements Using Multiscale Spatial Filters |
A Convolutional Neural Network Hand Tracker |
Correlation and Interpolation Networks for Real-Time Expression Analysis/Synthesis |
Learning Direction in Global Motion: Two Classes of Psychophysically-Motivated Models |
Associative Decorrelation Dynamics: A Theory of Self-Organization and Optimization in Feedback Networks |
JPMAX: Learning to Recognize Moving Objects as a Model-Fitting Problem |
PCA-Pyramids for Image Compression |
Unsupervised Classification of 3D Objects from 2D Views |
New Algorithms for 2D And 3D Point Matching: Pose Estimation and Correspondence |
Using a Neural Net to Instantiate a Deformable Model |
Nonlinear Image Interpolation Using Manifold Learning |
Coarse-to-Fine Image Search Using Neural Networks |
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition |
Learning Prototype Models for Tangent Distance |
Real-Time Control of Tokamak Plasma Using Neural Networks |
Recognizing Handwritten Digits Using Mixtures of Linear Models |
Optimal Movement Primitives |
An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems |
A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing |
Predictive Coding with Neural Nets: Application to Text Compression |
Predicting the Risk of Complications in Coronary Artery Bypass Operations Using Neural Networks |
Comparing the Prediction Accuracy of Artificial Neural Networks and Other Statistical Models for Breast Cancer Survival |
Learning to Play the Game of Chess |
A Mixture Model System for Medical and Machine Diagnosis |
Inferring Ground Truth from Subjective Labelling of Venus Images |
The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System |
Adaptive Elastic Input Field for Recognition Improvement |
Pairwise Neural Network Classifiers with Probabilistic Outputs |
Interference in Learning Internal Models of Inverse Dynamics in Humans |
Computational Structure of Coordinate Transformations: A Generalization Study |
Author Index |
Contents |
Donors |
NIPS foundation |
Committees |
Learning first-order Markov models for control / Andrew Ng |
A Large Deviation Bound for the Area Under the ROC Curve / Shivani Agarwal ; Dan Roth |
Learning Preferences for Multiclass Problems / Fabio Aiolli ; Alessandro Sperduti |
Harmonising Chorales by Probabilistic Inference / Moray Allan |
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces / Dragomir Anguelov ; Praveen Srinivasan ; Hoi-Cheung Pang ; James Davis |
A Direct Formulation for Sparse PCA Using Semidefinite Programming / Alexandre d'Aspremont ; Gert R. G. Lanckriet |
Comparing Beliefs, Surveys, and Random Walks / Erik Aurell ; Uri Gordon ; Scott Kirkpatrick |
The power of feature clustering: An application to object detection / Shai Avidan ; Moshe Butman |
Blind One-microphone Speech Separation: A Spectral Learning Approach |
Computing regularization paths for learning multiple kernels / Romain Thibaux |
Breaking SVM Complexity with Cross-Training / Gokhan H. Bakir |
Co-Training and Expansion: Towards Bridging Theory and Practice / Maria-Florina Balcan ; Avrim Blum ; Ke Yang |
Large-Scale Prediction of Disulphide Bond Connectivity / Pierre Baldi ; Jianlin Cheng ; Alessandro Vullo |
Spike Sorting: Bayesian Clustering of Non-Stationary Data / Adam Spiro ; Eran Stark |
Exponentiated Gradient Algorithms for Large-margin Structured Classification / Michael Collins ; David A. McAllester |
Maximising Sensitivity in a Spiking Network / Anthony J. Bell ; Lucas Parra |
Non-Local Manifold Tangent Learning / Martin Monperrus |
Who's in the Picture / Tamara L. Berg ; Alexander C. Berg ; Jaety Edwards ; David Forsyth |
At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks / Nils Bertschinger ; Robert Legenstein |
A Second Order Cone programming Formulation for Classifying Missing Data / Chiranjib Bhattacharyya ; Pannagadatta K. Shivaswamy ; Alex Smola |
Support Vector Classification with Input Data Uncertainty / Jinbo Bi |
Responding to Modalities with Different Latencies / Fredrik Bissmarck ; Hiroyuki Nakahara ; Okihide Hikosaka |
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis / Tobias Blaschke ; Laurenz Wiskott |
Hierarchical Distributed Representations for Statistical Language Modeling / John Blitzer ; Kilian Weinberger ; Lawrence Saul ; Fernando C. N. Pereira |
Markov Networks for Detecting Overlapping Elements in Sequence Data / Joseph Bockhorst ; Mark Craven |
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity / Sander. M. Bohte ; Michael C Mozer |
Convergence and No-Regret in Multiagent Learning / Michael Bowling |
Dependent Gaussian Processes / Phillip Boyle ; Marcus Frean |
Proximity Graphs for Clustering and Manifold Learning / Miguel A. Carreira-Perpinan ; Richard S. Zemel |
Incremental Algorithms for Hierarchical Classifications / Nicolo Cesa-Bianchi ; Andrea Tironi ; Luca Zaniboni |
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms |
Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation / Shantanu Chakrabartty ; Gert Cauwenberghs |
A Machine Learning Approach to Conjoint Analysis / Zaid Harchaoui |
Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) / Kumar Chellapilla ; Patrice Y. Simard |
Hierarchical Eigensolver for Transition Matrices in Spectral Methods / Chakra Chennubhotla ; Allan Jepson |
Modeling Conversational Dynamics as a Mixed-Memory Markov Process / Tanzeem Choudhury ; Sumit Basu |
Theories of Access Consciousness / Michael D. Colagrosso |
Distributed Information Regularization on Graphs / Adrian Corduneanu |
Confidence Intervals for the Area Under the ROC Curve |
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account / Nathaniel D. Daw |
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM / Juan Jose del Coz ; Gustavo F. Bayon ; Jorge Diez ; Oscar Luaces ; Antonio Bahamonde ; Carlos Sanudo |
Semigroup Kernals on Finite Sets / Marco Cuturi ; Jean-Philippe Vert |
Analysis of a greedy active learning strategy |
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees |
Bayesian inference in spiking neurons / Sophie Deneve |
Triangle Fixing Algorithms for the Metric Nearness Problem / Inderjit S. Dhillon ; Suvrit Sra ; Joel Tropp |
Pictorial Structures for Molecular Modeling: Interpreting Density Maps / Frank DiMaio ; Jude Shavlik ; George Phillips |
Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units / Eizaburo Doi ; Michael S. Lewicki |
Making Latin Manuscripts Searchable using gHMM's / Roger Bock ; Michael Maire ; Grace Vesom |
Seeing through Water / Alexei Efros ; Volkan Isler ; Jianbo Shi ; Mirko Visontai |
Experts in a Markov Decision Process / Eyal Even-Dar ; Yishay Mansour |
Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments |
A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees |
Learning Hyper-Features for Visual Identification / Andras D. Ferencz ; Erik G. Learned-Miller ; Jitendra Malik |
Sampling Methods for Unsupervised Learning / Rob Fergus |
On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks / Miguel Figueroa ; Seth Bridges ; Chris Diorio |
Object Classification from a Single Example Utilizing Class Relevance Metrics |
A Hidden Markov Model for de Novo Peptide Sequencing / Jonas Grossmann ; Sacha Baginsky ; Wilhelm Gruissem ; Franz Roos ; Peter Widmayer |
Implicit Wiener Series for Higher-Order Image Analysis / Matthias O. Franz |
Joint Probabilistic Curve Clustering and Alignment / Scott J. Gaffney |
Discriminant Saliency for Visual Recognition from Cluttered Scenes / Dashan Gao |
Instance-Based Relevance Feedback for Image Retrieval / Giorgio Giacinto ; Fabio Roli |
Euclidean Embedding of Co-Occurrence Data |
Hierarchical Clustering of a Mixture Model / Jacob Goldberger |
Neighbourhood Components Analysis / Ruslan Salakhutdinov |
Parallel Support Vector Machines: The Cascade SVM / Hans-Peter Graf ; Eric Cosatto ; Igor Dourdanovic ; Vladimir Vapnik |
Semi-Supervised Learning by Entropy Minimization |
Integrating Topics and Syntax / Mark Steyvers ; David M. Blei |
Result Analysis of the NIPS 2003 Feature Selection Challenge / Isabelle Guyon ; Steve Gunn ; Asa Ben-Hur ; Gideon Dror |
Theory of localized synfire chain: characteristic propagation speed of stable spike pattern / Kosuke Hamaguchi ; Kazuyuki Aihara |
The Entire Regulation Path for the Support Vector Machine / Robert Tibshirani |
An Auditory Paradigm for Brain-Computer Interfaces / N. Jeremy Hill ; Karin Bierig ; Niels Birbaumer |
The Cerebellum Chip: an Analog VLSI Implementation of a Cerebellar Model of Classical Conditioning / Constanze Hofstoetter ; Manuel Gil ; Kynan Eng ; Giacomo Indiveri ; Matti Mintz ; Jorg Kramer ; Paul F.M.J. Verschure |
Schema Learning: Experience-Based Construction of Predictive Action Models / Michael P. Holmes ; Charles Lee Isbell, Jr. |
Unsupervised Variational Bayesian Learning of Nonlinear Models / Antti Honkela ; Harri Valpola |
A Generalized Bradley-Terry Model: From Group Competition to Individual Skill / Tzu-Kuo Huang |
Message Errors in Belief Propagation / John W. Fisher |
Parametric Embedding for Class Visualization / Tomoharu Iwata ; Kazumi Saito ; Naonori Ueda |
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernal Feature Space / Robert Jenssen ; Deniz Erdogmus ; Jose C. Principe ; Torbjorn Eltoft |
Economic Properties of Social Networks / Robin Pemantle ; Siddharth Suri |
Online Bounds for Bayesian Algorithms |
Maximal Margin Labeling for Multi-Topic Text Categorization / Hideto Kazawa ; Tomonori Izumitani ; Hirotoshi Taira |
Generalization Error and Algorithmic Convergence of Median Boosting / Balazs Kegl |
Boosting on Manifolds: Adaptive Regularization of Base Classifiers / Ligen Wang |
Face Detection -- Efficient and Rank Deficient / Wolf Kienzle |
Neural Networks Computation by In Vitro Transcriptional Circuits / Jongmin Kim ; John Hopfield ; Erik Winfree |
Synchronization of neural networks by mutual learning and its application to cryptography / Einat Klein ; Rachel Mislovaty ; Ido Kanter ; Andreas Ruttor ; Wolfgang Kinzel |
Nearly Tight Bounds for the Continuum-Armed Bandit Problem / Robert D. Kleinberg |
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging / Vladimir Koltchinski ; Manel Martinez-Ramon ; Stefan Posse |
Newscast EM / Wojtek Kowalczyk |
On Semi-Supervised Classification / Balaji Krishnapuram ; David Williams ; Ya Xue ; Alexander Hartemink ; Lawrence Carin ; Mario Figueiredo |
An Application of Boosting to Graph Classification / Taku Kudo ; Yuji Matsumoto |
Methods Towards Invasive Human Brain Computer Interfaces / Thilo Hinterberger ; Guido Widman ; Michael Schroder ; Wolfgang Rosenstiel ; Christian E. Elger |
Beat Tracking the Graphical Model Way / Dustin Lang ; Nando de Freitas |
Semi-supervised Learning via Gaussian Processes |
Joint MRI Bias Removal Using Entropy Minimization Across Images / Parvez Ahammad |
Rate- and Phase-coded Autoassociative Memory / Mate Lengyel |
Maximum Likelihood Estimation of Intrinsic Dimension / Elizaveta Levina ; Peter J. Bickel |
Planning for Markov Decision Processes with Sparse Stochasticity / Geoff Gordon |
Incremental Learning for Visual Tracking / Jongwoo Lim ; David A, Ross ; Ruei-Sung Lin ; Ming-Hsuan Yang |
Adaptive Discriminative Generative Model and Its Applications |
Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation / Yuanqing Lin ; Daniel D. Lee |
Multiple Alignment of Continuous Time Series / Jennifer Listgarten ; Andrew Emili |
An Investigation of Practical Approximate Nearest Neighbor Algorithms |
Mistake Bounds for Maximum Entropy Discrimination / Phillip M. Long ; Xinyu Wu |
A Three Tiered Approach for Articulated Object Action Modeling and Recognition / Le Lu ; Gregory D. Hager ; Laurent Younes |
Semi-supervised Learning with Penalized Probabilistic Clustering / Zhengdong Lu |
Limits of Spectral Clustering / Ulrike de Luxburg ; Mikhail Belkin |
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits |
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms / Omid Madani ; David M. Pennock ; Gary William Flake |
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data / Mario Marchand ; Mohak Shah |
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters / Tim K. Marks ; John Hershey ; J. Cooper Roddey |
Linear Multilayer Independent Component Analysis for Large Natural Scenes / Yoshitatsu Matsuda ; Kazunori Yamaguchi |
Conditional Models of Identity Uncertainty with Application to Noun Coreference / Ben Wellner |
Multiple Relational Embedding / Roland Memisevic |
Kernels for Multi--task Learning / Charles A. Micchelli ; Massimiliano Pontil |
A Topographic Support Vector Machine: Classification Using Local Label Configurations / Johannes Mohr |
Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity / Marcelo A. Montemurro ; Stefano Panzeri |
Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks / Joris M. Mooij ; Hilbert J. Kappen |
Common-Frame Model for Object Recognition / Pierre Moreels |
Optimal sub-graphical models / Mukund Narasimhan |
Detecting Significant Multidimensional Spatial Clusters / Francisco Pereira ; Tom Mitchell |
Stable adaptive control with online learning |
Mass Meta-analysis in Talairach Space / Finn Arup Nielsen |
A Harmonic Excitation State-Space Approach to Blind Separation of Speech / Rasmus Kongsgaard Olsson ; Lars Kai Hansen |
Expectation Consistent Free Energies for Approximate Inference |
Discrete profile alignment via constrained information bottleneck / Sean O'Rourke ; Robin Friedman |
Synergistic Face Detection and Pose Estimation with Energy-Based Models / Margarita Osadchy ; Matthew L. Miller ; Yann LeCun |
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning |
Variational Minimax Estimation of Discrete Distributions under KL Loss |
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution / Hyun Jin Park ; Te-Won Lee |
Approximately Efficient Online Mechanism Design / Satinder P. Singh ; Dimah Yanovsky |
Efficient Out-of-Sample Extension of Dominant-Set Clusters / Massimiliano Pavan ; Marcello Pelillo |
A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound / Dori Peleg |
Active Learning for Anomaly and Rare-Category Detection / Dan Pelleg |
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs / Pascal PouPart |
New Criteria and a New Algorithm for Learning in Multi-Agent Systems / Rob Powers ; Yoav Shoham |
Conditional Random Fields for Object Recognition / Ariadna Quattoni ; Trevor Darrell |
Chemosensory Processing in a Spiking Model of the Olfactory Bulb: Chemotopic Convergence and Center Surround Inhibition / Baranidharan Raman ; Ricardo Gutierrez-Osuna |
Hierarchical Bayesian Inference in Networks of Spiking Neurons / Rajesh P. N. Rao |
An Information Maximization Model of Eye Movements / Walker Renninger ; James M. Coughlan ; Preeti Verghese |
Brain Inspired Reinforcement Learning / Francois Rivest ; John Kalaska |
Coarticulation in Markov Decision Processes / Khashayar Rohanimanesh ; Robert Platt ; Sridhar Mahadevan ; Roderic Grupen |
Learning, Regularization and Ill-Posed Inverse Problems / Lorenzo Rosasco ; Andrea Caponnetto ; Ernesto De Vito ; Francesca Odone ; Umberto de Giovannini |
Following Curved Regularized Optimization Solution Paths |
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning / Hui Zou |
Outlier Detection with One-class Kernel Fisher Discriminants |
Semi-parametric Exponential Family PCA / Sajama ; Alon Orlitsky |
Semi-Markov Conditional Random Fields for Information Extraction / Sunita Sarawagi ; William W. Cohen |
Kernel Methods for Implicit Surface Modeling / Joachim Giesen ; Simon Spalinger |
Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid / Felix Schurmann ; Karlheinz Meier ; Johannes Schemmel |
Learning Gaussian Process Kernels via Hierarchical Bayes / Kai Yu |
Assignment of Multiplicative Mixtures in Natural Images / Odelia Schwartz ; Terrence J. Sejnowski |
On the Adaptive Properties of Decision Trees |
Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization / Fei Sha |
Probabilistic Inference of Alternative Splicing Events in Microarray Data / Ofer Shai ; Qun Pan ; Christine Misquitta ; Benjamin J. Blencowe |
Resolving Perceptual Aliasing In The Presence Of Noisy Sensors / Guy Shani ; Ronen I. Brafman |
Algebraic Set Kernels with Application to Inference Over Local Image Representations / Amnon Shashua ; Tamir Hazan |
Dynamic Bayesian Networks for Brain-Computer Interfaces / Pradeep Shenoy |
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities / Lavi Shpigelman ; Rony Paz ; Eilon Vaadia |
Intrinsically Motivated Reinforcement Learning / Andrew G. Barto ; Nuttapong Chentanez |
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters / Evan Smith |
Learning Syntactic Patterns for Automatic Hypernym Discovery / Rion Snow ; Daniel Jurafsky |
Surface Reconstruction using Learned Shape Models / Jan Erik Solem ; Fredrik Kahl |
Using the Equivalent Kernel to Understand Gaussian Process Regression / Peter Sollich |
Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices / Noga Alon |
Maximum-Margin Matrix Factorization / Jason D. M. Rennie |
Density Level Detection is Classification / Don Hush ; Clint Scovel |
Fast Rates to Bayes for Kernel Machines |
Modelling Uncertainty in the Game of Go / David H. Stern ; David J. C. MacKay |
Constraining a Bayesian Model of Human Visual Speed Perception / Alan Stocker |
Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation / Michael Mandel |
Temporal-Difference Networks / Richard S. Sutton ; Brian Tanner |
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes |
Heuristics for Ordering Cue Search in Decision Making / Peter M. Todd ; Anja Dieckmann |
Contextual Models for Object Detection Using Boosted Random Fields / Kevin P. Murphy |
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model / Taro Toyoizumi ; Jean-Pascal Pfister ; Wulfram Gerstner |
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons / Jochen Triesch |
Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection |
Supervised Graph Inference / Yoshihiro Yamanishi |
Binet-Cauchy Kernels / S. V. N. Vishwanathan |
Instance-Specific Bayesian Model Averaging for Classification / Shyam Visweswaran ; Gregory F. Cooper |
Saliency-Driven Image Acuity Modulation on a Reconfigurable Array of Spiking Silicon Neurons / R. Jacob Vogelstein ; Udayan Mallik ; Eugenio Culurciello |
Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale / Haidong Wang ; Eran Segal ; Douglas L. Brutlag |
Adaptive Manifold Learning / Jing Wang ; Zhenyue Zhang ; Hongyuan Zha |
Exponential Family Harmoniums with an Application to Information Retrieval / Michal Rosen-Zvi |
Machine Learning Applied to Perception: Decision Images for Gender Classification / Heinrich H. Bulthoff |
The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data / Oliver M. C. Williams ; Andrew Blake ; Roberto Cipolla |
Generative Affine Localisation and Tracking / John Winn |
L_0-norm Minimization for Basis Selection / Bhaskar D. Rao |
Multi-agent Cooperation in Diverse Population Games / K. Y. M. Wong ; S. W. Lim ; Z. Gao |
Efficient Kernel Discriminant Analysis via QR Decomposition / Tao Xiong ; Jieping Ye ; Qi Li ; Ravi Janardan ; Vladimir Cherkassky |
Maximum Margin Clustering / Linli Xu ; James Neufeld ; Bryce Larson ; Dale Schuurmans |
Using Random Forests in the Structured Language Model / Peng Xu ; Frederick Jelinek |
Solitaire: Man Versus Machine / Xiang Yan ; Persi Diaconis ; Paat Rusmevichientong |
Efficient Kernel Machines Using the Improved Fast Gauss Transform / Changjiang Yang ; Ramani Duraiswami ; Larry Davis |
Two-Dimensional Linear Discriminant Analysis |
Inference, Attention, and Decision in a Bayesian Neural Architecture / Angela J. Yu |
The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters / Alan Yuille |
The Convergence of Contrastive Divergences |
Self-Tuning Spectral Clustering / Lihi Zelnik-Manor |
Probabilistic Computation in Spiking Populations / Quentin J. M. Huys ; Rama Natarajan |
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection / Jian Zhang ; Yiming Yang |
Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification |
Semi-supervised Learning on Directed Graphs |
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning / Xiaojin Zhu ; John Lafferty |
Kernel Projection Machine: a New Tool for Pattern Recognition / Laurent Zwald ; Regis Vert ; Gilles Blanchard ; Pascal Massart |
Subject Index |
Learning the Structure of Similarity |
A Model of Spatial Representations in Parietal Cortex Explains Hemineglect |
Human Reading and the Curse of Dimensionality |
Extracting Tree-structured Representations of Trained Networks |
Harmony Networks Do Not Work |
Dynamics of Attention as Near Saddle-node Bifurcation Behavior |
Rapid Quality Estimation of Neural Network Input Representations |
A Model of Auditory Streaming |
Modeling Interactions of the Rat's Place and Head Direction Systems |
Correlated Neuronal Response: Time Scales and Mechanisms |
Information through a Spiking Neuron |
Reorganization of Somatosensory Cortex after Tactile Training |
A Dynamical Model of Context Dependencies for the Vestibulo-Ocular Reflex |
The Role of Activity in Synaptic Competition at the Neuromuscular Junction |
When Is an Integrate-and-fire Neuron like a Poisson Neuron? |
How Perception Guides Production in Birdsong Learning |
The Geometry of Eye Rotations and Listing's Law |
Temporal Coding in the Submillisecond Range: Model of Barn Owl Auditory Pathway |
Cholinergic Suppression of Transmission May Allow Combined Associative Memory Function and Self-organization in the Neocortex |
A Predictive Switching Model of Cerebellar Movement Control |
Independent Component Analysis of Electroencephalographic Data |
Simulation of a Thalamocortical Circuit for Computing Directional Heading in the Rat |
Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision |
Learning Model Bias |
Statistical Theory of Overtraining -- Is Cross-Validation Asymptotically Effective? |
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-test Split |
Learning with Ensembles: How Overfitting Can Be Useful |
Neural Networks with Quadratic VC Dimension |
Sample Complexity for Learning Recurrent Perceptron Mappings |
On the Computational Power of Noisy Spiking Neurons |
A Realizable Learning Task Which Exhibits Overfitting |
Stable Dynamic Parameter Adaptation |
Estimating the Bayes Risk from Sample Data |
Recursive Estimation of Dynamic Modular RBF Networks |
On Neural Networks with Minimal Weights |
Modern Analytic Techniques to Solve the Dynamics of Recurrent Neural Networks |
Implementation Issues in the Fourier Transform Algorithm |
Generalisation of a Class of Continuous Neural Networks |
Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks |
Optimization Principles for the Neural Code |
Strong Unimodality and Exact Learning of Constant Depth 5-Perceptron Networks |
Active Learning in Multilayer Perceptrons |
Dynamics of On-line Gradient Descent Learning for Multilayer Neural Networks |
Worst-case Loss Bounds for Single Neurons |
Exponentially Many Local Minima for Single Neurons |
Adaptive Back-Propagation in On-line Learning of Multilayer Networks |
Optimizing Cortical Mappings |
Quadratic-type Lyapunov Functions for Competitive Neural Networks with Different Time-scales |
Examples of Learning Curves from a Modified VC-formalism |
Bayesian Methods for Mixtures of Experts |
Some Results on Convergent Unlearning Algorithm |
Geometry of Early Stopping in Linear Networks |
Absence of Cycles in Symmetric Neural Networks |
Adaptive Mixture of Probabilistic Transducers |
REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities -- Application to Transition-based Connectionist Speech Recognition |
Recurrent Neural Networks for Missing or Asynchronous Data |
Family Discovery |
Discriminant Adaptive Nearest Neighbor Classification and Regression |
Clustering Data through an Analogy to the Potts Model |
Generalized Learning Vector Quantization |
Stochastic Hillclimbing as a Baseline Method for Evaluating Genetic Algorithms |
Symplectic Nonlinear Component Analysis |
A Unified Learning Scheme: Bayesian-Kuilback Ying-Yang Machine |
Universal Approximation and Learning of Trajectories Using Oscillators |
A Smoothing Regularizer for Recurrent Neural Networks |
EM Optimization of Latent-Variable Density Models |
Factorial Hidden Markov Models |
Boosting Decision Trees |
Exploiting Tractable Substructures in Intractable Networks |
Hierarchical Recurrent Neural Networks for Long-term Dependencies |
Discovering Structure in Continuous Variables Using Bayesian Networks |
Using Pairs of Data Points to Define Splits for Decision Trees |
Gaussian Processes for Regression |
Pruning with Generalization Based Weight Saliencies: ?OBD, ?OBS |
Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks |
Generating Accurate and Diverse Members of a Neural-network Ensemble |
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging |
Explorations with the Dynamic Wave Model |
The Capacity of a Bump |
Tempering Backpropagation Networks: Not All Weights Are Created Equal |
Investment Learning with Hierarchical PSOMS |
Learning Long-term Dependencies Is Not as Difficult with NARX Networks |
Constructive Algorithms for Hierarchical Mixtures of Experts |
An Information-theoretic Learning Algorithm for Neural Network Classification |
A Practical Monte Carlo Implementation of Bayesian Learning |
From Isolation to Cooperation: An Alternative View of a System of Experts |
Finite State Automata that Recurrent Cascade-Correlation Cannot Represent |
SPERT-II: A Vector Microprocessor System and Its Application to Large Problems in Backpropagation Training |
Softassign versus Softmax: Benchmarks in Combinatorial Optimization |
A Multiscale Attentional Framework for Relaxation Neural Networks |
Is Learning the n-th Thing Any Easier Than Learning the First? |
Using Unlabeled Data for Supervised Learning |
Learning Sparse Perceptrons |
Does the Wake-sleep Algorithm Produce Good Density Estimators? |
Improved Silicon Cochlea Using Compatible Lateral Bipolar Transistors |
Adaptive Retina with Center-Surround Receptive Field |
Neuron-MOS Temporal Winner Search Hardware for Fully-parallel Data Processing |
Analog VLSI Processor Implementing the Continuous Wavelet Transform |
Silicon Models for Auditory Scene Analysis |
VLSI Model of Primate Visual Smooth Pursuit |
Model Matching and SFMD Computation |
Parallel Analog VLSI Architectures for Computation of Heading Direction and Time-to-contact |
Onset-based Sound Segmentation |
Laterally Interconnected Self-organizing Maps in Handwritten Digit Recognition |
Forward-backward Retraining of Recurrent Neural Networks |
Context-dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System |
A New Learning Algorithm for Blind Signal Separation |
Handwritten Word Recognition Using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models |
Selective Attention for Handwritten Digit Recognition |
|
OCR Alphanumeric Handprint Module |
The Gamma MLP for Speech Phoneme Recognition |
Vision |
A Framework for Nonrigid Matching and Correspondence |
Control of Selective Visual Attention: Modeling the "Where" Pathway |
Unsupervised Pixel-prediction |
Learning to Predict Visibility and Invisibility from Occlusion Events |
Classifying Facial Action |
Modeling Saccadic Targeting in Visual Search |
A Model of Transparent Motion and Non-transparent Motion Aftereffects |
A Neural Network Model of 3-D Lightness Perception |
Empirical Entropy Manipulation for Real-world Problems |
Active Gesture Recognition Using Learned Visual Attention |
Seemore: A View-based Approach to 3-D Object Recognition Using Multiple Visual Cues |
Human Face Detection in Visual Scenes |
Improving Committee Diagnosis with Resampling Techniques |
Primitive Manipulation Learning with Connectionism |
Beating a Defender in Robotic Soccer: Memory-based Learning of a Continuous Function |
Visual Gesture-based Robot Guidance with a Modular Neural System |
A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network |
Prediction of Beta Sheets in Proteins |
A Neural Network Autoassociator for Induction Motor Failure Prediction |
Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence |
A Neural Network Classifier for the I1000 OCR Chip |
Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control |
Optimal Asset Allocation Using Adaptive Dynamic Programming |
Using the Future to "Sort Out" the Present: Rankprop and Multitask Learning for Medical Risk Evaluation |
Stock Selection via Nonlinear Multi-factor Models |
Experiments with Neural Networks for Real Time Implementation of Control |
High-speed Airborne Particle Monitoring Using Artificial Neural Networks |
Control |
A Dynamical Systems Approach for a Learnable Autonomous Robot |
Parallel Optimization of Motion Controllers via Policy Iteration |
Learning Fine Motion by Markov Mixtures of Experts |
Neural Control for Nonlinear Dynamic Systems |
Improving Elevator Performance Using Reinforcement Learning |
High-performance Job-Shop Scheduling with a Time-delay TD(?) Network |
Competence Acquisition in an Autonomous Mobile Robot Using Hardware Neural Techniques |
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding |
Stable Linear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions |
Stable Fitted Reinforcement Learning |
Improving Policies without Measuring Merits |
Memory-based Stochastic Optimization |
Temporal Difference in Learning in Continuous Time and Space |
Reinforcement Learning by Probability Matching |
NIPS Foundation |
Learning vehicular dynamics, with application to modeling helicopters / Varun Ganapathi |
Policy-Gradient Methods for Planning / Douglas Aberdeen |
Kernelized Infomax Clustering |
Large-scale biophysical parameter estimation in single neurons via constrained linear regression / Misha Ahrens |
Maximum Margin Semi-Supervised Learning for Structured Variables / Yasemin Altun |
Large scale networks fingerprinting and visualization using the k-core decomposition / J. Ignacio Alvarez-Hamelin ; Luca Dall'Asta ; Alain Barrat ; Alessandro Vespignani |
Fast Information Value for Graphical Models / Brigham Anderson ; Andrew Moore |
A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D Objects / David Arathorn |
Combining Graph Laplacians for Semi-Supervised Learning / Andreas Argyriou ; Mark Herbster |
Learning in Silicon: Timing is Everything |
On Local Rewards and Scaling Distributed Reinforcement Learning |
Bayesian models of human action understanding / Chris Baker ; Josh Tenenbaum ; Rebecca Saxe |
The Curse of Highly Variable Functions for Local Kernel Machines |
Non-Local Manifold Parzen Windows / Hugo Larochelle |
Convex Neural Networks / Patrice Marcotte |
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction / Masashi Sugiyama ; Motoaki Kawanabe ; Vladimir Spokoiny |
From Weighted Classification to Policy Search / Doron Blatt ; Alfred Hero |
Correlated Topic Models |
Saliency Based on Information Maximization / Neil Bruce ; John Tsotsos |
Active Learning For Identifying Function Threshold Boundaries / Brent Bryan ; Robert Nichol ; Christopher Miller ; Christopher Genovese ; Larry Wasserman |
Subsequence Kernels for Relation Extraction / Razvan Bunescu ; Raymond J. Mooney |
Faster Rates in Regression via Active Learning / Rui Castro ; Rebecca Willett |
Gradient Flow Independent Component Analysis in Micropower VLSI / Abdullah Celik ; Milutin Stanacevic |
Improved risk tail bounds for on-line algorithms |
Layered Dynamic Textures / Antoni Chan |
Size Regularized Cut for Data Clustering / Yixin Chen ; Ya Zhang ; Xiang Ji |
Learning from Data of Variable Quality / Jennifer Wortman |
Efficient estimation of hidden state dynamics from spike trains |
Coarse sample complexity bounds for active learning |
Norepinephrine and Neural Interrupts |
Fast Krylov Methods fo N-Body Learning / Yang Wang ; Maryam Mahdaviani |
The Forgetron: A Kernel-Based Perceptron on a Fixed Budget |
Data-Driven Online to Batch Conversations |
Beyond Gaussian Processes: On the Distributions of Infinite Networks / Ricky Der ; Daniel Lee |
Generalized Nonnegative Matrix Approximations with Bregman |
An Application of Markov Random Fields to Range Sensing / James Diebel |
Transfer Learning for text classification / Chuong Do |
A Theoretical Analysis of Robust Coding over Noisy Overcomplete / Doru C. Balcan |
Optimizing spatio-temporal filters for improving Brain-Computer Interfacing / Matthias Krauledat ; Florian Losch |
Correcting sample selection bias in maximum entropy density estimation |
Searching for Character Models |
Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps / Austin Eliazar ; Parr Ronald |
Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Models / Yaakov Engel ; Peter Szabo ; Dmitry Volkinshtein |
Two view learning: SVM-2K, Theory and Practice / Jason D. R. Farquhar ; David R. Hardoon ; Hongying Meng ; Sandor Szedmak |
Robust design of biological experiments / Patrick Flaherty ; Michael Jordan ; Adam Arkin |
Pattern Recognition from One Example by Chopping / Francois Fleuret |
Mixture Modeling by Affinity Propagation / Delbert Dueck |
Statistical Convergence of Kernel CCA |
Learning Rankings via Convex Hull Separation / Glenn M. Fung ; Romer Rosales |
A Connectionist Model for Constructive Modal Reasoning / Dov Gabbay |
Large-Scale Multiclass Transduction |
Products of "Edge-perts" / Peter Gehler |
Fast biped walking with a reflexive controller and real-time policy searching / Tao Geng |
Bayesian Sets / Katherine Heller |
Query by Committee Made Real / Ran Gilad-Bachrach ; Amir Navot |
Metric Learning by Collapsing Classes |
Interpolating between types and tokens by estimating power-law generators / Sharon Goldwater ; Mark Johnson |
A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification |
Infinite latent feature models and the Indian buffet process |
Computing the Solution Path for the Regularized Support Vector Regression / Lacey Gunther |
Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs / Firas Hamze |
Tensor Subspace Analysis / Deng Cai |
Laplacian Score for Feature Selection |
Inferring Motor Programs from Images of Handwritten Digits / Vinod Nair |
Response Analysis of Neuronal Population with Synaptic Depression / Wentao Huang ; Licheng Jiao ; Shan Tan ; Maoguo Gong |
Non-iterative Estimation with Perturbed Gaussian Markov Processes / Yunsong Huang ; B. Keith Jenkins |
Learning Cue-Invariant Visual Responses / Jarmo Hurri |
Bayesian Surprise Attracts Human Attention / Laurent Itti |
Efficient Estimation of OOMs / Herbert Jaeger ; Mingjie Zhao ; Andreas Kolling |
Representing Part-Whole Relationships in Recurent Neural Networks / Viren Jain ; Valentin Zhigulin |
A Probabilistic Approach for Optimizing Spectral Clustering / Rong Jin ; Chris Ding ; Feng Kang |
Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation / Jason Johnson ; Dmitry Malioutov |
Using "epitomes" to model genetic diversity: Rational design of HIV vaccine cocktails / Nebojsa Jojic ; Vladimir Jojic ; Christopher Meek ; David Heckerman |
Integrate-and-Fire models with adaptation are good enough / Renaud Jolivet ; Alexander Rauch ; Hans-Rudolf Luscher |
Generalization Error Bounds for Aggregation by Mirror Descent with Averaging / Anatoli Juditsky ; Alexander Nazin ; Alexandre Tsybakov ; Nicolas Vayatis |
From Batch to Transductive Online Learning / Adam Kalai |
Worst-Case Bounds for Gaussian Process Models / Matthias W. Seeger ; Dean P. Foster |
Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification / Ashish Kapoor ; Hyungil Ahn ; Rosalind W. Picard |
Is Early Vision Optimized for Extracting Higher-order Dependencies? / Yan Karklin |
A matching pursuit approach to sparse Gaussian process regression / S. Sathiya Keerthi ; Wei Chu |
Benchmarking Non-Parametric Statistical Tests / Mikaela Keller ; Siew Yeung Wong |
Robust Fisher Discriminant Analysis / Seung-Jean Kim ; Alessandro Magnani ; Stephen Boyd |
Measuring Shared Information and Coordinated Activity in Neuronal Networks / Kristina Klinkner ; Cosma Shalizi ; Marcelo Camperi |
Inference with Minimal Communication: a Decision-Theoretic Variational Approach / O. Patrick Kreidl |
Generalization in Clustering with Unobserved Features / Eyal Krupka |
Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery / Jeremy Kubica ; Joseph Masiero ; Robert Jedicke ; Andrew Connolly |
Assessing Approximations for Gaussian Process Classification |
Rodeo: Sparse Nonparametric Regression in High Dimensions |
Fixing two weaknesses of the Spectral Method / Kevin Lang |
Fusion of Similarity Data in Clustering |
A PAC-Bayes approach to the Set Covering Machine / Francois Laviolette |
Off-Road Obstacle Avoidance through End-to-End Learning / Urs Muller ; Jan Ben ; Beat Flepp |
Dual-Tree Fast Gauss Transforms / Dongryeol Lee |
CMOL CrossNets: Possible Neuromorphic Nanoelectronic Circuits / Jung Hoon Lee ; Xiaolong Ma ; Konstantin Likharev |
A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity |
Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches / Ann Levina ; Michael Herrmann |
From Lasso regression to Feature vector machine / Fan Li ; Eric Xing |
Location-based activity recognition / Lin Liao ; Dieter Fox ; Henry Kautz |
Radial Basis Function Network for Multi-task Learning / Xuejun Liao |
Asymptotics of Gaussian Regularized Least Squares / Ross Lipert ; Ryan Rifkin |
Efficient Unsupervised Learning for Localization and Detection in Object Categories / Nicolas Loeff ; Himanshu Arora ; Alexander Sorokin |
Convergence and Consistency of Regularized Boosting Algorithms with Stationary ss-Mixing Observations |
Ideal Observers for Detecting Motion: Correspondence Noise / Hongjing Lu |
Principles of real-time computing with feedback applied to cortical microcircuit models / Prashant Joshi ; Eduardo D. Sontag |
Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions / Mauro Maggioni |
Noise and the two-thirds power Law / Uri Maoz ; Elon Portugaly ; Tamar Flash |
Modeling Memory Transfer and Saving in Cerebellar Motor Learning / Naoki Masuda |
An exploration-exploitation model based on norepinepherine and dopamine activity / Samuel McClure ; Mark Gilzenrat ; Jonathan D. Cohen |
Online Discovery and Learning of Predictive State Representations / Peter McCracken |
An Alternative Infinite Mixture of Gaussian Process Experts / Edward Meeds ; Simon Osindero |
Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments / Keiji Miura |
Concensus Propagation |
Context as Filtering / Daichi Mochihashi |
Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms / Baback Moghaddam |
Top-Down Control of Visual Attention: A Rational Account / Michael Shettel ; Shaun P. Vecera |
Rate Distortion Codes in Sensor Networks / Tatsuto Murayama ; Peter Davis |
Gaussian Processes for Multiuser Detection in CDMA receivers |
Nested sampling for Potts models / Ian Muray ; David MacKay ; John Skilling |
Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators / Boaz Nadler ; Stephane Lafon ; Ronald Coifman ; Ioannis Kevrekidis |
Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity / Srikantan Nagarajan ; Hagai Attias ; Kenneth Hild ; Kensuke Sekihara |
An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Achitecture / Yusuke Nakashita ; Yoshio Mita |
Q-Clustering |
Optimal cue selection strategy / Vidhya Navalpakkam |
Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity |
A Bayesian Spatial Scan Statistic |
Divergences, surrogate loss functions and experimental design / AnLong Nguyen ; Martin J. Wainwright |
How fast to work: Response vigor, motivation and tonic dopamine / Yael Niv |
Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction / Guido Nolte ; Andreas Ziehe ; Frank Meinecke |
An Approximate Inference Approach for the PCA Reconstruction Error |
Bayesian model learning in human visual perception / Gergo Orban ; Jozsef Fiser ; Richard N. Aslin |
Spiking Inputs to a Winner-take-all Network / Matthias Oster ; Shih-Chii Liu |
Variational EM Algorithms for Non-Gaussian Latent Variable Models / Kenneth Kreutz-Delgado |
Nonparametric inference of prior probabilities from Bayes-optimal behavior |
Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI / Ofer Pasternak ; Nir Sochen ; Nathan Intrator ; Yaniv Assaf |
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects |
Scaling Laws in Natural Scenes and the Inference of 3D Shape |
Off-policy Learning with Options and Recognizers / Brian Potetz ; Cosmin Paduraru ; Anna Koop ; Doina Precup |
Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization / Maxim Raginsky ; Svetlana Lazebnik |
Preconditioner Approximations for Probabilistic Graphical Models / Pradeep Ravikumar |
Cue Integration for Figure/Ground Labeling / Xiaofeng Ren ; Charless Fowlkes |
Generalization to Unseen Cases / Teemu Roos ; Peter D. Grunwald ; Petri Myllymaki ; Henry Tirri |
Visual Encoding with Jittering Eyes / Michele Rucci |
Dynamic Social Network Analysis using Latent Space Models / Purnamrita Sarkar |
Logic and MRF Circuitry for Labeling Occluding and Thinline Visual Contours / Eric Saund |
Learning Depth from Single Monocular Images / Ashutosh Saxena ; Sung H. Chung |
Identifying Distributed Object Representations in Human Extrastriate Visual Cortex / Rory Sayres ; David Ress ; Kalanit Grill-Spector |
On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal? / Michael Schmitt ; Laura Martignon |
Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation / Nicol N. Schraudolph ; Jin Yu |
The Information-Form Data Association Filter / Brad Schumitsch ; Gary Bradski ; Kunle Olukotun |
A Bayesian Framework for Tilt Perception and Confidence / Terrence Sejnowski |
Learning Minimum Volume Sets |
AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems |
Fast Gaussian Process Regression using KD-Trees |
Learning Shared Latent Structure for Image Synthesis and Robotic Imitation / Aaron Shon ; Keith Grochow |
Selecting Landmark Points for Sparse Manifold Learning |
Conditional Visual Tracking in Kernel Space / Cristian Sminchisescu ; Atul Kanaujia ; Zhiguo Li ; Dimitri Metaxas |
Sparse Gaussian Processes using Pseudo-inputs |
Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface / Le Song ; Evian Gordon ; Elly Gysels |
A General and Efficient Multiple Kernel Learning Algorithm |
Prediction and Change Detection / Scott Brown |
Sensory Adaptation within a Bayesian Framework for Perception |
Describing Visual Scenes using Transformed Dirichlet Processes / William Freeman |
Active Learning for Misspecified Models |
Temporal |
Abstraction in Temporal-difference Networks / Eddie Rafols |
Sequence and Tree Kernels with Statistical Feature Mining / Hideki Isozaki |
Silicon growth cones map silicon retina / Brian Taba |
Temporally changing synaptic plasticity / Minija Tamosiunaite |
Structured Prediction via the Extragradient Method / Simon Lacoste-Julien |
Affine Structure From Sound |
Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares / Jo-Anne Ting ; Aaron D'Souza ; Kenji Yamamoto ; Toshinori Yoshioka ; Donna L. Hoffman ; Shinji Kakei ; Lauren Sergio ; Mitsuo Kawato ; Peter L. Strick ; Stefan Schaal |
Generalization error bounds for classifiers trained with interdependent data / Nicolas Usunier ; Massih-Reza Amini ; Patrick Gallinari |
TD(0) Leads to Better Policies than Approximate Value Iteration |
An aVLSI Cricket Ear Model / Andre Van Schaik ; Richard Reeve ; Craig Jin ; Tara Hamilton |
Goal-Based Imitation as Probabilistic Inference over Graphical Models / Deepak Verma |
Kernels for gene regulatory regions / Robert A. F. Thurman ; William Stafford Noble |
Consistency of one-class SVM and related algorithms |
Multiple Instance Boosting for Object Detection / Paul Viola ; John Platt ; Cha Zhang |
Estimating the wrong Markov random field: Benefits in the computation-limited setting |
Recovery of Jointly Sparse Signals from Few Random Projections / Michael Wakin ; Marco Duarte ; Shriram Sarvotham ; Dror Baron ; Richard G. Baraniuk |
Gaussian Pocess Dynamical Models / Jack Wang ; David Fleet |
Group and Topic Discovery from Relations and Their Attributes / Natasha Mohanty |
A Bayes Rule for Density Matrices |
Variational Bayesian Stochastic Complexity of Mixture Models / Kazuho Watanabe ; Sumio Watanabe |
Distance Metric Learning for Large Margin Nearest Neighbor Classification |
Analyzing Auditory Neurons by Learning Distance Functions / Inna Weiner ; Israel Nelken |
Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games / Gabriel Y. Weintraub ; C. Lanier Benkard |
Active Bidirectional Coupling in a Cochlear Chip / Bo Wen |
Neural mechanisms of contrast dependent receptive field size in V1 / Jim Wielaard ; Paul Sajda |
Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care / John Quinn ; Neil McIntosh |
Comparing the Effects of Different Weight Distributions on Finding Sparse Representations |
Message passing for task redistribution on sparse graphs / David Saad ; Zhuo Gao |
Modeling Neural Population Spiking Activity with Gibbs Distributions / Frank Wood ; Stefan Roth ; Michael Block |
Extracting Dynamical Structure Embedded in Neural Activity / Byron Yu ; Afsheen Afshar ; Gopal Santhanam ; Stephen I. Ryu ; Krishna V. Shenoy |
Soft Clustering on Graphs / Shipeng Yu |
Augmented Rescorla-Wagner and Maximum Likelihood Estimation |
The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search / Gregory Zelinsky ; Wei Zhang ; Bing Yu ; Xin Chen ; Dimitris Samaras |
Learning Influence among Interacting Markov Chains / Dong Zhang ; Deb Roy ; Daniel Gatica-Perez |
Learning Multiple Related Tasks using Latent Independent Component Analysis |
Modeling Neuronal Interactivity using Dynamic Bayesian Networks / Lei Zhang ; Nelly Alia-Klein ; Nora Volkow ; Rita Goldstein |
Analysis of Spectral Kernel Design based Semi-supervised Learning / Rie Ando |
A Computational Model of Eye Movements during Object Class Detection / Hyejin Yang |
Separation of Music Signals by Harmonic Structure Modeling / Yun-Gang Zhang ; Chang-Shui Zhang |
A Domain Decomposition Method for Fast Manifold Learning |
A Hierarchical Compositional System for Rapid Object Detection / Long Zhu |
Cyclic Equilibria in Markov Games / Martin Zinkevich ; Amy Greenwald ; Michael L. Littman |
On the Convergence of Eigenspacesin Kernel Principal Component Analysis |