Book
Advances in Neural Information Processing Systems 16 (NIPS 2003)
Edited by:
S. Thrun and L. Saul and B. Schölkopf
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
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