Book

Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels Ryan Kelly, Tai Sing Lee

Linear Response for Approximate Inference Max Welling, Yee Teh

Wormholes Improve Contrastive Divergence Max Welling, Andriy Mnih, Geoffrey E. Hinton

Probability Estimates for Multi-Class Classification by Pairwise Coupling Ting-fan Wu, Chih-jen Lin, Ruby Weng

Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons Thomas Natschläger, Wolfgang Maass

Mutual Boosting for Contextual Inference Michael Fink, Pietro Perona

On the Dynamics of Boosting Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire

Distributed Optimization in Adaptive Networks Ciamac C. Moallemi, Benjamin Roy

Statistical Debugging of Sampled Programs Alice Zheng, Michael Jordan, Ben Liblit, Alex Aiken

A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications Pedro Moreno, Purdy Ho, Nuno Vasconcelos

A Model for Learning the Semantics of Pictures Victor Lavrenko, R. Manmatha, Jiwoon Jeon

The Diffusion-Limited Biochemical Signal-Relay Channel Peter Thomas, Donald Spencer, Sierra Hampton, Peter Park, Joseph Zurkus

Margin Maximizing Loss Functions Saharon Rosset, Ji Zhu, Trevor Hastie

Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models Radford Neal, Matthew Beal, Sam Roweis

Self-calibrating Probability Forecasting Vladimir Vovk, Glenn Shafer, Ilia Nouretdinov

Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses Adria Bofill-i-petit, Alan Murray

Semi-supervised Protein Classification Using Cluster Kernels Jason Weston, Dengyong Zhou, André Elisseeff, William Noble, Christina Leslie

When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? David Donoho, Victoria Stodden

A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning Maneesh Sahani

Online Classification on a Budget Koby Crammer, Jaz Kandola, Yoram Singer

Pairwise Clustering and Graphical Models Noam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss

Link Prediction in Relational Data Ben Taskar, Ming-fai Wong, Pieter Abbeel, Daphne Koller

Human and Ideal Observers for Detecting Image Curves Fang Fang, Daniel Kersten, Paul R. Schrater, Alan L. Yuille

Linear Program Approximations for Factored Continuous-State Markov Decision Processes Milos Hauskrecht, Branislav Kveton

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

Log-Linear Models for Label Ranking Ofer Dekel, Yoram Singer, Christopher D. Manning

Learning the k in k-means Greg Hamerly, Charles Elkan

Learning a Rare Event Detection Cascade by Direct Feature Selection Jianxin Wu, James M. Rehg, Matthew Mullin

Non-linear CCA and PCA by Alignment of Local Models Jakob Verbeek, Sam Roweis, Nikos Vlassis

Unsupervised Context Sensitive Language Acquisition from a Large Corpus Zach Solan, David Horn, Eytan Ruppin, Shimon Edelman

Modeling User Rating Profiles For Collaborative Filtering Benjamin M. Marlin

Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System Marc Toussaint

Bias-Corrected Bootstrap and Model Uncertainty Harald Steck, Tommi Jaakkola

Nonlinear Processing in LGN Neurons Vincent Bonin, Valerio Mante, Matteo Carandini

Ranking on Data Manifolds Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf

Approximate Analytical Bootstrap Averages for Support Vector Classifiers Dörthe Malzahn, Manfred Opper

An Infinity-sample Theory for Multi-category Large Margin Classification Tong Zhang

A Neuromorphic Multi-chip Model of a Disparity Selective Complex Cell Bertram Shi, Eric Tsang

Robustness in Markov Decision Problems with Uncertain Transition Matrices Arnab Nilim, Laurent Ghaoui

Parameterized Novelty Detectors for Environmental Sensor Monitoring Cynthia Archer, Todd Leen, António Baptista

Sensory Modality Segregation Virginia Sa

Nonstationary Covariance Functions for Gaussian Process Regression Christopher Paciorek, Mark Schervish

Algorithms for Interdependent Security Games Michael Kearns, Luis E. Ortiz

How to Combine Expert (and Novice) Advice when Actions Impact the Environment? Daniela de Farias, Nimrod Megiddo

Reasoning about Time and Knowledge in Neural Symbolic Learning Systems Artur Garcez, Luis Lamb

Policy Search by Dynamic Programming J. Bagnell, Sham M. Kakade, Jeff Schneider, Andrew Ng

A Holistic Approach to Compositional Semantics: a connectionist model and robot experiments Yuuya Sugita, Jun Tani

Semidefinite Relaxations for Approximate Inference on Graphs with Cycles Michael Jordan, Martin J. Wainwright

Discriminating Deformable Shape Classes Salvador Ruiz-correa, Linda Shapiro, Marina Meila, Gabriel Berson

Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA David Hoyle, Magnus Rattray

Auction Mechanism Design for Multi-Robot Coordination Curt Bererton, Geoffrey J. Gordon, Sebastian Thrun

Geometric Analysis of Constrained Curves Anuj Srivastava, Washington Mio, Xiuwen Liu, Eric Klassen

A Low-Power Analog VLSI Visual Collision Detector Reid Harrison

An Improved Scheme for Detection and Labelling in Johansson Displays Claudio Fanti, Marzia Polito, Pietro Perona

1-norm Support Vector Machines Ji Zhu, Saharon Rosset, Robert Tibshirani, Trevor Hastie

Envelope-based Planning in Relational MDPs Natalia Gardiol, Leslie Kaelbling

Necessary Intransitive Likelihood-Ratio Classifiers Gang Ji, Jeff A. Bilmes

Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles Mark Girolami, Ata Kabán

Bounded Finite State Controllers Pascal Poupart, Craig Boutilier

Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds Ingo Steinwart

Towards Social Robots: Automatic Evaluation of Human-Robot Interaction by Facial Expression Classification G.C. Littlewort, M.S. Bartlett, I.R. Fasel, J. Chenu, T. Kanda, H. Ishiguro, J.R. Movellan

Entrainment of Silicon Central Pattern Generators for Legged Locomotory Control Francesco Tenore, Ralph Etienne-Cummings, M. Lewis

Fast Embedding of Sparse Similarity Graphs John Platt

Online Passive-Aggressive Algorithms Shai Shalev-shwartz, Koby Crammer, Ofer Dekel, Yoram Singer

Training a Quantum Neural Network Bob Ricks, Dan Ventura

Perspectives on Sparse Bayesian Learning Jason Palmer, Bhaskar Rao, David Wipf

One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals Tomohiro Nakatani, Masato Miyoshi, Keisuke Kinoshita

Multiple Instance Learning via Disjunctive Programming Boosting Stuart Andrews, Thomas Hofmann

An Autonomous Robotic System for Mapping Abandoned Mines David Ferguson, Aaron Morris, Dirk Hähnel, Christopher Baker, Zachary Omohundro, Carlos Reverte, Scott Thayer, Charles Whittaker, William Whittaker, Wolfram Burgard, Sebastian Thrun

Model Uncertainty in Classical Conditioning Aaron C. Courville, Geoffrey J. Gordon, David Touretzky, Nathaniel Daw

Local Phase Coherence and the Perception of Blur Zhou Wang, Eero Simoncelli

New Algorithms for Efficient High Dimensional Non-parametric Classification Ting liu, Andrew Moore, Alexander Gray

Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates Peter Bartlett, Michael Jordan, Jon Mcauliffe

Design of Experiments via Information Theory Liam Paninski

Minimax Embeddings Matthew Brand

Efficient and Robust Feature Extraction by Maximum Margin Criterion Haifeng Li, Tao Jiang, Keshu Zhang

Training fMRI Classifiers to Detect Cognitive States across Multiple Human Subjects Xuerui Wang, Rebecca Hutchinson, Tom M. Mitchell

Applying Metric-Trees to Belief-Point POMDPs Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun

Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression Roland Vollgraf, Michael Scholz, Ian Meinertzhagen, Klaus Obermayer

Application of SVMs for Colour Classification and Collision Detection with AIBO Robots Michael Quinlan, Stephan Chalup, Richard Middleton

Warped Gaussian Processes Edward Snelson, Zoubin Ghahramani, Carl Rasmussen

Online Learning via Global Feedback for Phrase Recognition Xavier Carreras, Lluís Màrquez

Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian Eiji Mizutani, James Demmel

AUC Optimization vs. Error Rate Minimization Corinna Cortes, Mehryar Mohri

Semi-Supervised Learning with Trees Charles Kemp, Thomas Griffiths, Sean Stromsten, Joshua Tenenbaum

Finding the M Most Probable Configurations using Loopy Belief Propagation Chen Yanover, Yair Weiss

A Nonlinear Predictive State Representation Matthew Rudary, Satinder Singh

A Recurrent Model of Orientation Maps with Simple and Complex Cells Paul Merolla, Kwabena A. Boahen

Predicting Speech Intelligibility from a Population of Neurons Jeff Bondy, Ian Bruce, Suzanna Becker, Simon Haykin

Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales Saori Tanaka, Kenji Doya, Go Okada, Kazutaka Ueda, Yasumasa Okamoto, Shigeto Yamawaki

Measure Based Regularization Olivier Bousquet, Olivier Chapelle, Matthias Hein

Geometric Clustering Using the Information Bottleneck Method Susanne Still, William Bialek, Léon Bottou

Sample Propagation Mark Paskin

Gaussian Processes in Reinforcement Learning Malte Kuss, Carl Rasmussen

The Doubly Balanced Network of Spiking Neurons: A Memory Model with High Capacity Yuval Aviel, David Horn, Moshe Abeles

Hierarchical Topic Models and the Nested Chinese Restaurant Process Thomas Griffiths, Michael Jordan, Joshua Tenenbaum, David Blei

A Sampled Texture Prior for Image Super-Resolution Lyndsey Pickup, Stephen J. Roberts, Andrew Zisserman

Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic Biophysics Bernd Porr, Ausra Saudargiene, Florentin Wörgötter

Sparse Greedy Minimax Probability Machine Classification Thomas R. Strohmann, Andrei Belitski, Gregory Grudic, Dennis DeCoste

Approximate Policy Iteration with a Policy Language Bias Alan Fern, Sungwook Yoon, Robert Givan

Information Bottleneck for Gaussian Variables Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss

Laplace Propagation Eleazar Eskin, Alex Smola, S.v.n. Vishwanathan

Error Bounds for Transductive Learning via Compression and Clustering Philip Derbeko, Ran El-Yaniv, Ron Meir

Approximate Expectation Maximization Tom Heskes, Onno Zoeter, Wim Wiegerinck

A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters Daniel Neill, Andrew Moore

Computing Gaussian Mixture Models with EM Using Equivalence Constraints Noam Shental, Aharon Bar-hillel, Tomer Hertz, Daphna Weinshall

Convex Methods for Transduction Tijl Bie, Nello Cristianini

Kernel Dimensionality Reduction for Supervised Learning Kenji Fukumizu, Francis Bach, Michael Jordan

Learning with Local and Global Consistency Dengyong Zhou, Olivier Bousquet, Thomas Lal, Jason Weston, Bernhard Schölkopf

Max-Margin Markov Networks Ben Taskar, Carlos Guestrin, Daphne Koller

Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence Amit Gruber, Yair Weiss

Sequential Bayesian Kernel Regression Jaco Vermaak, Simon Godsill, Arnaud Doucet

PAC-Bayesian Generic Chaining Jean-yves Audibert, Olivier Bousquet

Ambiguous Model Learning Made Unambiguous with 1/f Priors Gurinder Atwal, William Bialek

Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data Amos J. Storkey

Can We Learn to Beat the Best Stock Allan Borodin, Ran El-Yaniv, Vincent Gogan

An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science Woojae Kim, Daniel Navarro, Mark Pitt, In Myung

Dynamical Modeling with Kernels for Nonlinear Time Series Prediction Liva Ralaivola, Florence d'Alché-Buc

Learning Non-Rigid 3D Shape from 2D Motion Lorenzo Torresani, Aaron Hertzmann, Christoph Bregler

Discriminative Fields for Modeling Spatial Dependencies in Natural Images Sanjiv Kumar, Martial Hebert

Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis Pedro Felzenszwalb, Daniel Huttenlocher, Jon Kleinberg

A Probabilistic Model of Auditory Space Representation in the Barn Owl Brian Fischer, Charles Anderson

Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data Neil Lawrence

Tree-structured Approximations by Expectation Propagation Yuan Qi, Tom Minka

Boosting versus Covering Kohei Hatano, Manfred K. K. Warmuth

Learning Near-Pareto-Optimal Conventions in Polynomial Time Xiaofeng Wang, Tuomas Sandholm

Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes Kevin P. Murphy, Antonio Torralba, William Freeman

Approximability of Probability Distributions Alina Beygelzimer, Irina Rish

Gene Expression Clustering with Functional Mixture Models Darya Chudova, Christopher Hart, Eric Mjolsness, Padhraic Smyth

Large Scale Online Learning Léon Bottou, Yann Cun

Plasticity Kernels and Temporal Statistics Peter Dayan, Michael Häusser, Michael London

Phonetic Speaker Recognition with Support Vector Machines William Campbell, Joseph Campbell, Douglas Reynolds, Douglas Jones, Timothy Leek

Information Maximization in Noisy Channels : A Variational Approach David Barber, Felix Agakov

Variational Linear Response Manfred Opper, Ole Winther

Circuit Optimization Predicts Dynamic Networks for Chemosensory Orientation in Nematode C. elegans Nathan A. Dunn, John S. Conery, Shawn Lockery

Learning to Find Pre-Images Jason Weston, Bernhard Schölkopf, Gökhan Bakir

Sparse Representation and Its Applications in Blind Source Separation Yuanqing Li, Shun-ichi Amari, Sergei Shishkin, Jianting Cao, Fanji Gu, Andrzej Cichocki

Probabilistic Inference in Human Sensorimotor Processing Konrad Körding, Daniel M. Wolpert

From Algorithmic to Subjective Randomness Thomas Griffiths, Joshua Tenenbaum

Eye Micro-movements Improve Stimulus Detection Beyond the Nyquist Limit in the Peripheral Retina Matthias Hennig, Florentin Wörgötter

Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron? Yoichi Miyawaki, Masato Okada

Efficient Multiscale Sampling from Products of Gaussian Mixtures Alexander Ihler, Erik Sudderth, William Freeman, Alan Willsky

Markov Models for Automated ECG Interval Analysis Nicholas Hughes, Lionel Tarassenko, Stephen J. Roberts

A Mixed-Signal VLSI for Real-Time Generation of Edge-Based Image Vectors Masakazu Yagi, Hideo Yamasaki, Tadashi Shibata

Autonomous Helicopter Flight via Reinforcement Learning H. Kim, Michael Jordan, Shankar Sastry, Andrew Ng

Insights from Machine Learning Applied to Human Visual Classification Felix A. Wichmann, Arnulf Graf

Classification with Hybrid Generative/Discriminative Models Rajat Raina, Yirong Shen, Andrew McCallum, Andrew Ng

Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms Claudio Gentile

Feature Selection in Clustering Problems Volker Roth, Tilman Lange

Optimal Manifold Representation of Data: An Information Theoretic Approach Denis Chigirev, William Bialek

Invariant Pattern Recognition by Semi-Definite Programming Machines Thore Graepel, Ralf Herbrich

Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interface Yu Zhou, Steven Mason, Gary Birch

Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron Sung Jun, Barak Pearlmutter

Image Reconstruction by Linear Programming Koji Tsuda, Gunnar Rätsch

Extreme Components Analysis Max Welling, Christopher Williams, Felix Agakov

Bayesian Color Constancy with Non-Gaussian Models Charles Rosenberg, Alok Ladsariya, Tom Minka

All learning is Local: Multi-agent Learning in Global Reward Games Yu-han Chang, Tracey Ho, Leslie Kaelbling

Automatic Annotation of Everyday Movements Deva Ramanan, David Forsyth

A Classification-based Cocktail-party Processor Nicoleta Roman, Deliang Wang, Guy Brown

Linear Dependent Dimensionality Reduction Nathan Srebro, Tommi Jaakkola

Clustering with the Connectivity Kernel Bernd Fischer, Volker Roth, Joachim Buhmann

Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation Leonid Sigal, Michael Isard, Benjamin Sigelman, Michael Black

Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering Yoshua Bengio, Jean-françcois Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Roux, Marie Ouimet

Learning Spectral Clustering Francis Bach, Michael Jordan

Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model Liam Paninski, Eero Simoncelli, Jonathan Pillow

Prediction on Spike Data Using Kernel Algorithms Jan Eichhorn, Andreas Tolias, Alexander Zien, Malte Kuss, Jason Weston, Nikos Logothetis, Bernhard Schölkopf, Carl Rasmussen

An MDP-Based Approach to Online Mechanism Design David C. Parkes, Satinder Singh

Probabilistic Inference of Speech Signals from Phaseless Spectrograms Kannan Achan, Sam Roweis, Brendan J. Frey

Denoising and Untangling Graphs Using Degree Priors Quaid Morris, Brendan J. Frey

Learning a Distance Metric from Relative Comparisons Matthew Schultz, Thorsten Joachims

Locality Preserving Projections Xiaofei He, Partha Niyogi

Unsupervised Color Decomposition Of Histologically Stained Tissue Samples Andrew Rabinovich, Sameer Agarwal, Casey Laris, Jeffrey Price, Serge Belongie

Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons Hsin Chen, Patrice Fleury, Alan Murray

Eye Movements for Reward Maximization Nathan Sprague, Dana Ballard

Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter Kazuyuki Samejima, Kenji Doya, Yasumasa Ueda, Minoru Kimura

ICA-based Clustering of Genes from Microarray Expression Data Su-in Lee, Serafim Batzoglou

On the Concentration of Expectation and Approximate Inference in Layered Networks XuanLong Nguyen, Michael Jordan

Identifying Structure across Pre-partitioned Data Zvika Marx, Ido Dagan, Eli Shamir

Eigenvoice Speaker Adaptation via Composite Kernel Principal Component Analysis James Kwok, Brian Mak, Simon Ho

A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural Systems Z. Shi, Timothy Horiuchi

Extending Q-Learning to General Adaptive Multi-Agent Systems Gerald Tesauro

No Unbiased Estimator of the Variance of K-Fold Cross-Validation Yoshua Bengio, Yves Grandvalet

GPPS: A Gaussian Process Positioning System for Cellular Networks Anton Schwaighofer, Marian Grigoras, Volker Tresp, Clemens Hoffmann

Reconstructing MEG Sources with Unknown Correlations Maneesh Sahani, Srikantan Nagarajan

Increase Information Transfer Rates in BCI by CSP Extension to Multi-class Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller

Dopamine Modulation in a Basal Ganglio-Cortical Network of Working Memory Aaron Gruber, Peter Dayan, Boris Gutkin, Sara Solla

Approximate Planning in POMDPs with Macro-Actions Georgios Theocharous, Leslie Kaelbling

ARA*: Anytime A* with Provable Bounds on Sub-Optimality Maxim Likhachev, Geoffrey J. Gordon, Sebastian Thrun

Salient Boundary Detection using Ratio Contour Song Wang, Toshiro Kubota, Jeffrey Siskind

Semi-Definite Programming by Perceptron Learning Thore Graepel, Ralf Herbrich, Andriy Kharechko, John Shawe-taylor

An Iterative Improvement Procedure for Hierarchical Clustering David Kauchak, Sanjoy Dasgupta

Kernels for Structured Natural Language Data Jun Suzuki, Yutaka Sasaki, Eisaku Maeda

Near-Minimax Optimal Classification with Dyadic Classification Trees Clayton Scott, Robert Nowak

Bounded Invariance and the Formation of Place Fields Reto Wyss, Paul Verschure

Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks Justin Werfel, Xiaohui Xie, H. Seung

Learning Bounds for a Generalized Family of Bayesian Posterior Distributions Tong Zhang

A Functional Architecture for Motion Pattern Processing in MSTd Scott Beardsley, Lucia Vaina

Online Learning of Non-stationary Sequences Claire Monteleoni, Tommi Jaakkola

Advances in Neural Information Processing Systems 16 (NIPS 2003)

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