Advances in Neural Information Processing Systems 15

NIPS 2002

Edited by S. Becker and S. Thrun and K. Obermayer

207 papers

Temporal Coherence, Natural Image Sequences, and the Visual Cortex Jarmo Hurri, Aapo Hyvärinen
Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach Christopher G. Atkeson, Jun Morimoto
A Differential Semantics for Jointree Algorithms James D. Park, Adnan Darwiche
"Name That Song!" A Probabilistic Approach to Querying on Music and Text Brochu Eric, Nando de Freitas
Automatic Derivation of Statistical Algorithms: The EM Family and Beyond Bernd Fischer, Johann Schumann, Wray Buntine, Alexander G. Gray
Going Metric: Denoising Pairwise Data Volker Roth, Julian Laub, Klaus-Robert Müller, Joachim M. Buhmann
String Kernels, Fisher Kernels and Finite State Automata Craig Saunders, Alexei Vinokourov, John S. Shawe-taylor
Extracting Relevant Structures with Side Information Gal Chechik, Naftali Tishby
Classifying Patterns of Visual Motion - a Neuromorphic Approach Jakob Heinzle, Alan Stocker
How the Poverty of the Stimulus Solves the Poverty of the Stimulus Willem H. Zuidema
Fast Transformation-Invariant Factor Analysis Anitha Kannan, Nebojsa Jojic, Brendan Frey
Spikernels: Embedding Spiking Neurons in Inner-Product Spaces Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia
Graph-Driven Feature Extraction From Microarray Data Using Diffusion Kernels and Kernel CCA Jean-philippe Vert, Minoru Kanehisa
Spike Timing-Dependent Plasticity in the Address Domain R. J. Vogelstein, Francesco Tenore, Ralf Philipp, Miriam S. Adlerstein, David H. Goldberg, Gert Cauwenberghs
Efficient Learning Equilibrium Ronen I. Brafman, Moshe Tennenholtz
Using Tarjan's Red Rule for Fast Dependency Tree Construction Dan Pelleg, Andrew W. Moore
Approximate Inference and Protein-Folding Chen Yanover, Yair Weiss
Learning a Forward Model of a Reflex Bernd Porr, Florentin Wörgötter
Information Regularization with Partially Labeled Data Martin Szummer, Tommi S. Jaakkola
Intrinsic Dimension Estimation Using Packing Numbers Balázs Kégl
Mismatch String Kernels for SVM Protein Classification Eleazar Eskin, Jason Weston, William S. Noble, Christina S. Leslie
Adaptive Caching by Refetching Robert B. Gramacy, Manfred K. Warmuth, Scott A. Brandt, Ismail Ari
Timing and Partial Observability in the Dopamine System Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
Multiple Cause Vector Quantization David A. Ross, Richard S. Zemel
Unsupervised Color Constancy Kinh Tieu, Erik G. Miller
Value-Directed Compression of POMDPs Pascal Poupart, Craig Boutilier
Constraint Classification for Multiclass Classification and Ranking Sariel Har-Peled, Dan Roth, Dav Zimak
Neural Decoding of Cursor Motion Using a Kalman Filter W Wu, M. J. Black, Y. Gao, M. Serruya, A. Shaikhouni, J. P. Donoghue, Elie Bienenstock
On the Dirichlet Prior and Bayesian Regularization Harald Steck, Tommi S. Jaakkola
Scaling of Probability-Based Optimization Algorithms J. L. Shapiro
Forward-Decoding Kernel-Based Phone Recognition Shantanu Chakrabartty, Gert Cauwenberghs
Optoelectronic Implementation of a FitzHugh-Nagumo Neural Model Alexandre R. Romariz, Kelvin Wagner
Margin-Based Algorithms for Information Filtering Nicolò Cesa-bianchi, Alex Conconi, Claudio Gentile
Half-Lives of EigenFlows for Spectral Clustering Chakra Chennubhotla, Allan D. Jepson
The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard A. Müller
Optimality of Reinforcement Learning Algorithms with Linear Function Approximation Ralf Schoknecht
Evidence Optimization Techniques for Estimating Stimulus-Response Functions Maneesh Sahani, Jennifer F. Linden
Binary Coding in Auditory Cortex Michael R. Deweese, Anthony M. Zador
Learning Attractor Landscapes for Learning Motor Primitives Auke J. Ijspeert, Jun Nakanishi, Stefan Schaal
Combining Dimensions and Features in Similarity-Based Representations Daniel J. Navarro, Michael D. Lee
Bayesian Monte Carlo Zoubin Ghahramani, Carl E. Rasmussen
A Model for Learning Variance Components of Natural Images Yan Karklin, Michael S. Lewicki
Effective Dimension and Generalization of Kernel Learning Tong Zhang
Nash Propagation for Loopy Graphical Games Luis E. Ortiz, Michael Kearns
Neuromorphic Bisable VLSI Synapses with Spike-Timing-Dependent Plasticity Giacomo Indiveri
Source Separation with a Sensor Array using Graphical Models and Subband Filtering Hagai Attias
Dopamine Induced Bistability Enhances Signal Processing in Spiny Neurons Aaron J. Gruber, Sara A. Solla, James C. Houk
An Information Theoretic Approach to the Functional Classification of Neurons Elad Schneidman, William Bialek, Michael Ii
An Asynchronous Hidden Markov Model for Audio-Visual Speech Recognition Samy Bengio
Shape Recipes: Scene Representations that Refer to the Image William T. Freeman, Antonio Torralba
Real-Time Particle Filters Cody Kwok, Dieter Fox, Marina Meila
Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting Kenji Fukumizu, Shotaro Akaho, Shun-ichi Amari
Manifold Parzen Windows Pascal Vincent, Yoshua Bengio
Parametric Mixture Models for Multi-Labeled Text Naonori Ueda, Kazumi Saito
Transductive and Inductive Methods for Approximate Gaussian Process Regression Anton Schwaighofer, Volker Tresp
Adapting Codes and Embeddings for Polychotomies Gunnar Rätsch, Sebastian Mika, Alex J. Smola
Topographic Map Formation by Silicon Growth Cones Brian Taba, Kwabena A. Boahen
Analysis of Information in Speech Based on MANOVA Sachin S. Kajarekar, Hynek Hermansky
Discriminative Binaural Sound Localization Ehud Ben-reuven, Yoram Singer
Fractional Belief Propagation Wim Wiegerinck, Tom Heskes
Stability-Based Model Selection Tilman Lange, Mikio L. Braun, Volker Roth, Joachim M. Buhmann
Hidden Markov Model of Cortical Synaptic Plasticity: Derivation of the Learning Rule Michael Eisele, Kenneth D. Miller
Automatic Alignment of Local Representations Yee W. Teh, Sam T. Roweis
Field-Programmable Learning Arrays Seth Bridges, Miguel Figueroa, Chris Diorio, David Hsu
Boosting Density Estimation Saharon Rosset, Eran Segal
Support Vector Machines for Multiple-Instance Learning Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann
Bias-Optimal Incremental Problem Solving Jürgen Schmidhuber
Rate Distortion Function in the Spin Glass State: A Toy Model Tatsuto Murayama, Masato Okada
Adaptive Nonlinear System Identification with Echo State Networks Herbert Jaeger
Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell, Yann L. Cun
An Impossibility Theorem for Clustering Jon M. Kleinberg
Visual Development Aids the Acquisition of Motion Velocity Sensitivities Robert A. Jacobs, Melissa Dominguez
On the Complexity of Learning the Kernel Matrix Olivier Bousquet, Daniel Herrmann
Clustering with the Fisher Score Koji Tsuda, Motoaki Kawanabe, Klaus-Robert Müller
Artefactual Structure from Least-Squares Multidimensional Scaling Nicholas P. Hughes, David Lowe
Adaptation and Unsupervised Learning Peter Dayan, Maneesh Sahani, Gregoire Deback
Learning in Zero-Sum Team Markov Games Using Factored Value Functions Michail G. Lagoudakis, Ronald Parr
Convergence Properties of Some Spike-Triggered Analysis Techniques Liam Paninski
Learning to Take Concurrent Actions Khashayar Rohanimanesh, Sridhar Mahadevan
Handling Missing Data with Variational Bayesian Learning of ICA Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski
Ranking with Large Margin Principle: Two Approaches Amnon Shashua, Anat Levin
A Bilinear Model for Sparse Coding David B. Grimes, Rajesh P. N. Rao
Data-Dependent Bounds for Bayesian Mixture Methods Ron Meir, Tong Zhang
Information Diffusion Kernels Guy Lebanon, John D. Lafferty
Boosted Dyadic Kernel Discriminants Baback Moghaddam, Gregory Shakhnarovich
Derivative Observations in Gaussian Process Models of Dynamic Systems E. Solak, R. Murray-smith, W. E. Leithead, D. J. Leith, Carl E. Rasmussen
Global Versus Local Methods in Nonlinear Dimensionality Reduction Vin D. Silva, Joshua B. Tenenbaum
Learning Graphical Models with Mercer Kernels Francis R. Bach, Michael I. Jordan
Stochastic Neighbor Embedding Geoffrey E. Hinton, Sam T. Roweis
Learning in Spiking Neural Assemblies David Barber
A Model for Real-Time Computation in Generic Neural Microcircuits Wolfgang Maass, Thomas Natschläger, Henry Markram
Categorization Under Complexity: A Unified MDL Account of Human Learning of Regular and Irregular Categories David Fass, Jacob Feldman
Learning with Multiple Labels Rong Jin, Zoubin Ghahramani
Branching Law for Axons Dmitri B. Chklovskii, Armen Stepanyants
Dyadic Classification Trees via Structural Risk Minimization Clayton Scott, Robert Nowak
PAC-Bayes & Margins John Langford, John Shawe-Taylor
Dynamical Causal Learning David Danks, Thomas L. Griffiths, Joshua B. Tenenbaum
Maximally Informative Dimensions: Analyzing Neural Responses to Natural Signals Tatyana Sharpee, Nicole C. Rust, William Bialek
Fast Exact Inference with a Factored Model for Natural Language Parsing Dan Klein, Christopher D. Manning
Morton-Style Factorial Coding of Color in Primary Visual Cortex Javier R. Movellan, Thomas Wachtler, Thomas D. Albright, Terrence Sejnowski
One-Class LP Classifiers for Dissimilarity Representations Elzbieta Pekalska, David M.J. Tax, Robert Duin
Regularized Greedy Importance Sampling Finnegan Southey, Dale Schuurmans, Ali Ghodsi
Modeling Midazolam's Effect on the Hippocampus and Recognition Memory Kenneth J. Malmberg, René Zeelenberg, Richard M. Shiffrin
Fast Kernels for String and Tree Matching Alex J. Smola, S.v.n. Vishwanathan
Expected and Unexpected Uncertainty: ACh and NE in the Neocortex Peter Dayan, Angela J. Yu
Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers Sepp Hochreiter, Klaus Obermayer
Learning Semantic Similarity Jaz Kandola, Nello Cristianini, John S. Shawe-taylor
How Linear are Auditory Cortical Responses? Maneesh Sahani, Jennifer F. Linden
Incremental Gaussian Processes Joaquin Quiñonero-candela, Ole Winther
Dynamic Bayesian Networks with Deterministic Latent Tables David Barber
Generalized² Linear² Models Geoffrey J. Gordon
Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex Christian K. Machens, Michael Wehr, Anthony M. Zador
Bayesian Models of Inductive Generalization Neville E. Sanjana, Joshua B. Tenenbaum
Dynamical Constraints on Computing with Spike Timing in the Cortex Arunava Banerjee, Alexandre Pouget
Bayesian Estimation of Time-Frequency Coefficients for Audio Signal Enhancement Patrick J. Wolfe, Simon J. Godsill
Real-Time Monitoring of Complex Industrial Processes with Particle Filters Rubén Morales-Menéndez, Nando de Freitas, David Poole
Retinal Processing Emulation in a Programmable 2-Layer Analog Array Processor CMOS Chip R. Carmona, F. Jiménez-garrido, R. Dominguez-castro, S. Espejo, A. Rodriguez-vázquez
Bayesian Image Super-Resolution Michael E. Tipping, Christopher M. Bishop
Charting a Manifold Matthew Brand
A Minimal Intervention Principle for Coordinated Movement Emanuel Todorov, Michael I. Jordan
A Probabilistic Approach to Single Channel Blind Signal Separation Gil-jin Jang, Te-Won Lee
A Digital Antennal Lobe for Pattern Equalization: Analysis and Design Alex Holub, Gilles Laurent, Pietro Perona
Knowledge-Based Support Vector Machine Classifiers Glenn M. Fung, Olvi L. Mangasarian, Jude W. Shavlik
Conditional Models on the Ranking Poset Guy Lebanon, John D. Lafferty
A Formulation for Minimax Probability Machine Regression Thomas Strohmann, Gregory Z. Grudic
Multiclass Learning by Probabilistic Embeddings Ofer Dekel, Yoram Singer
Improving a Page Classifier with Anchor Extraction and Link Analysis William W. Cohen
VIBES: A Variational Inference Engine for Bayesian Networks Christopher M. Bishop, David Spiegelhalter, John Winn
A Convergent Form of Approximate Policy Iteration Theodore J. Perkins, Doina Precup
Mean Field Approach to a Probabilistic Model in Information Retrieval Bin Wu, K. Wong, David Bodoff
Exponential Family PCA for Belief Compression in POMDPs Nicholas Roy, Geoffrey J. Gordon
Dynamic Structure Super-Resolution Amos J. Storkey
Independent Components Analysis through Product Density Estimation Trevor Hastie, Rob Tibshirani
Discriminative Densities from Maximum Contrast Estimation Peter Meinicke, Thorsten Twellmann, Helge Ritter
Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior Patrik O. Hoyer, Aapo Hyvärinen
Combining Features for BCI Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller
A Probabilistic Model for Learning Concatenative Morphology Matthew G. Snover, Michael R. Brent
The Decision List Machine Marina Sokolova, Mario Marchand, Nathalie Japkowicz, John S. Shawe-taylor
How to Combine Color and Shape Information for 3D Object Recognition: Kernels do the Trick B. Caputo, Gy. Dorkó
Reconstructing Stimulus-Driven Neural Networks from Spike Times Duane Q. Nykamp
Selectivity and Metaplasticity in a Unified Calcium-Dependent Model Luk Chong Yeung, Brian S. Blais, Leon N. Cooper, Harel Z. Shouval
Learning to Detect Natural Image Boundaries Using Brightness and Texture David R. Martin, Charless C. Fowlkes, Jitendra Malik
Concurrent Object Recognition and Segmentation by Graph Partitioning Stella X. Yu, Ralph Gross, Jianbo Shi
Approximate Linear Programming for Average-Cost Dynamic Programming Benjamin V. Roy, Daniela D. Farias
Learning Sparse Topographic Representations with Products of Student-t Distributions Max Welling, Simon Osindero, Geoffrey E. Hinton
Margin Analysis of the LVQ Algorithm Koby Crammer, Ran Gilad-bachrach, Amir Navot, Naftali Tishby
Feature Selection by Maximum Marginal Diversity Nuno Vasconcelos
A Neural Edge-Detection Model for Enhanced Auditory Sensitivity in Modulated Noise Alon Fishbach, Bradford J. May
Concentration Inequalities for the Missing Mass and for Histogram Rule Error Luis E. Ortiz, David A. McAllester
Learning Sparse Multiscale Image Representations Phil Sallee, Bruno A. Olshausen
The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities Sumio Watanabe, Shun-ichi Amari
Learning About Multiple Objects in Images: Factorial Learning without Factorial Search Christopher K. I. Williams, Michalis K. Titsias
Distance Metric Learning with Application to Clustering with Side-Information Eric P. Xing, Michael I. Jordan, Stuart Russell, Andrew Y. Ng
Location Estimation with a Differential Update Network Ali Rahimi, Trevor Darrell
Hyperkernels Cheng S. Ong, Robert C. Williamson, Alex J. Smola
Prediction and Semantic Association Thomas L. Griffiths, Mark Steyvers
A Maximum Entropy Approach to Collaborative Filtering in Dynamic, Sparse, High-Dimensional Domains Dmitry Y. Pavlov, David M. Pennock
Annealing and the Rate Distortion Problem Albert E. Parker, Tomá\v S. Gedeon, Alexander G. Dimitrov
Self Supervised Boosting Max Welling, Richard S. Zemel, Geoffrey E. Hinton
An Estimation-Theoretic Framework for the Presentation of Multiple Stimuli Christian W. Eurich
Convergent Combinations of Reinforcement Learning with Linear Function Approximation Ralf Schoknecht, Artur Merke
Informed Projections David Cohn
Automatic Acquisition and Efficient Representation of Syntactic Structures Zach Solan, Eytan Ruppin, David Horn, Shimon Edelman
Application of Variational Bayesian Approach to Speech Recognition Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda
Stable Fixed Points of Loopy Belief Propagation Are Local Minima of the Bethe Free Energy Tom Heskes
Identity Uncertainty and Citation Matching Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart Russell, Ilya Shpitser
Fast Sparse Gaussian Process Methods: The Informative Vector Machine Neil D. Lawrence, Matthias Seeger, Ralf Herbrich
Recovering Articulated Model Topology from Observed Rigid Motion Leonid Taycher, John Iii, Trevor Darrell
Learning to Perceive Transparency from the Statistics of Natural Scenes Anat Levin, Assaf Zomet, Yair Weiss
Replay, Repair and Consolidation Szabolcs Káli, Peter Dayan
Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis Alexei Vinokourov, Nello Cristianini, John Shawe-Taylor
Cluster Kernels for Semi-Supervised Learning Olivier Chapelle, Jason Weston, Bernhard Schölkopf
A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences Eric P. Xing, Michael I. Jordan, Richard M. Karp, Stuart Russell
Speeding up the Parti-Game Algorithm Maxim Likhachev, Sven Koenig
Kernel-Based Extraction of Slow Features: Complex Cells Learn Disparity and Translation Invariance from Natural Images Alistair Bray, Dominique Martinez
Monaural Speech Separation Guoning Hu, Deliang Wang
Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines Fei Sha, Lawrence K. Saul, Daniel D. Lee
Kernel Design Using Boosting Koby Crammer, Joseph Keshet, Yoram Singer
Rational Kernels Corinna Cortes, Patrick Haffner, Mehryar Mohri
Linear Combinations of Optic Flow Vectors for Estimating Self-Motion - a Real-World Test of a Neural Model Matthias O. Franz, Javaan S. Chahl
Kernel Dependency Estimation Jason Weston, Olivier Chapelle, Vladimir Vapnik, André Elisseeff, Bernhard Schölkopf
Circuit Model of Short-Term Synaptic Dynamics Shih-Chii Liu, Malte Boegershausen, Pascal Suter
Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems Sepp Hochreiter, Michael Mozer, Klaus Obermayer
Robust Novelty Detection with Single-Class MPM Laurent E. Ghaoui, Michael I. Jordan, Gert R. Lanckriet
Binary Tuning is Optimal for Neural Rate Coding with High Temporal Resolution Matthias Bethge, David Rotermund, Klaus Pawelzik
Feature Selection in Mixture-Based Clustering Martin H. Law, Anil K. Jain, Mário Figueiredo
Minimax Differential Dynamic Programming: An Application to Robust Biped Walking Jun Morimoto, Christopher G. Atkeson
Theory-Based Causal Inference Joshua B. Tenenbaum, Thomas L. Griffiths
Learning to Classify Galaxy Shapes Using the EM Algorithm Sergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath
FloatBoost Learning for Classification Stan Z. Li, Zhenqiu Zhang, Heung-yeung Shum, Hongjiang Zhang
Adaptive Scaling for Feature Selection in SVMs Yves Grandvalet, Stéphane Canu
Adaptive Classification by Variational Kalman Filtering Peter Sykacek, Stephen J. Roberts
A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages Dörthe Malzahn, Manfred Opper
Developing Topography and Ocular Dominance Using Two aVLSI Vision Sensors and a Neurotrophic Model of Plasticity Terry Elliott, Jörg Kramer
Gaussian Process Priors with Uncertain Inputs Application to Multiple-Step Ahead Time Series Forecasting Agathe Girard, Carl Edward Rasmussen, Joaquin Quiñonero Candela, Roderick Murray-Smith
Maximum Likelihood and the Information Bottleneck Noam Slonim, Yair Weiss
The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum Christopher Williams, John S. Shawe-taylor
Adaptive Quantization and Density Estimation in Silicon David Hsu, Seth Bridges, Miguel Figueroa, Chris Diorio
Improving Transfer Rates in Brain Computer Interfacing: A Case Study Peter Meinicke, Matthias Kaper, Florian Hoppe, Manfred Heumann, Helge Ritter
Discriminative Learning for Label Sequences via Boosting Yasemin Altun, Thomas Hofmann, Mark Johnson
Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games Xiaofeng Wang, Tuomas Sandholm
Using Manifold Stucture for Partially Labeled Classification Mikhail Belkin, Partha Niyogi
Recovering Intrinsic Images from a Single Image Marshall F. Tappen, William T. Freeman, Edward H. Adelson
A Note on the Representational Incompatibility of Function Approximation and Factored Dynamics Eric Allender, Sanjeev Arora, Michael Kearns, Cristopher Moore, Alexander Russell
A Prototype for Automatic Recognition of Spontaneous Facial Actions M.S. Bartlett, G.C. Littlewort, T.J. Sejnowski, J.R. Movellan
Exact MAP Estimates by (Hyper)tree Agreement Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky
Prediction of Protein Topologies Using Generalized IOHMMs and RNNs Gianluca Pollastri, Pierre Baldi, Alessandro Vullo, Paolo Frasconi

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