Advances in Neural Information Processing Systems 16 (NIPS 2003)
The papers below appear in Advances in Neural Information Processing Systems 16 edited by S. Thrun and L.K. Saul and B. Schölkopf.They are proceedings from the conference, "Neural Information Processing Systems 2003."
- 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 Kabán
- Hierarchical Topic Models and the Nested Chinese Restaurant Process Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum, David M. Blei
- 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, Robert Tibshirani, Trevor J. Hastie
- Image Reconstruction by Linear Programming Koji Tsuda, Gunnar Rätsch
- Multiple Instance Learning via Disjunctive Programming Boosting Stuart Andrews, Thomas Hofmann
- Convex Methods for Transduction Tijl D. Bie, Nello Cristianini
- Kernel Dimensionality Reduction for Supervised Learning Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
- 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 R. Strohmann, Andrei Belitski, Gregory Z. 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'alché-buc
- Extreme Components Analysis Max Welling, Christopher Williams, Felix V. Agakov
- 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 Denny Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
- Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering Yoshua Bengio, Jean-françcois Paiement, Pascal Vincent, Olivier Delalleau, Nicolas L. Roux, Marie Ouimet
- Pairwise Clustering and Graphical Models Noam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss
- Tree-structured Approximations by Expectation Propagation Yuan Qi, Tom Minka
- Information Maximization in Noisy Channels : A Variational Approach David Barber, Felix V. Agakov
- Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian Eiji Mizutani, James Demmel
- Large Scale Online Learning Léon Bottou, Yann L. Cun
- Online Classification on a Budget Koby Crammer, Jaz Kandola, Yoram Singer
- Online Learning via Global Feedback for Phrase Recognition Xavier Carreras, Lluís Màrquez
- Sparse Representation and Its Applications in Blind Source Separation Yuanqing Li, Shun-ichi Amari, Sergei Shishkin, Jianting Cao, Fanji Gu, Andrzej S. Cichocki
- Perspectives on Sparse Bayesian Learning Jason Palmer, Bhaskar D. Rao, David P. Wipf
- Semi-Supervised Learning with Trees Charles Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum
- New Algorithms for Efficient High Dimensional Non-parametric Classification 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 using Loopy Belief Propagation Chen Yanover, Yair Weiss
- Non-linear CCA and PCA by Alignment of Local Models Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis
- Learning Spectral Clustering Francis R. Bach, Michael I. Jordan
- AUC Optimization vs. Error Rate Minimization Corinna Cortes, Mehryar Mohri
- Learning with Local and Global Consistency Denny Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, Bernhard Schölkopf
- Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data Neil D. Lawrence
- Warped Gaussian Processes Edward Snelson, Zoubin Ghahramani, Carl E. Rasmussen
- 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 Max Welling, Yee W. Teh
- Semidefinite Relaxations for Approximate Inference on Graphs with Cycles Michael I. Jordan, Martin J. 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 Long Nguyen, Michael I. Jordan
- Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models Radford M. Neal, Matthew J. Beal, Sam T. Roweis
- Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis Pedro F. Felzenszwalb, Daniel P. Huttenlocher, Jon M. Kleinberg
- Wormholes Improve Contrastive Divergence Max Welling, Andriy Mnih, Geoffrey E. Hinton
- Sample Propagation Mark A. Paskin
- Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data Amos J. Storkey
- Laplace Propagation Eleazar Eskin, Alex J. Smola, S.v.n. Vishwanathan
- Learning to Find Pre-Images Jason Weston, Bernhard Schölkopf, Gökhan H. Bakir
- Semi-Definite Programming by Perceptron Learning Thore Graepel, Ralf Herbrich, Andriy Kharechko, John S. Shawe-taylor
- Computing Gaussian Mixture Models with EM Using Equivalence Constraints Noam Shental, Aharon Bar-hillel, Tomer Hertz, Daphna Weinshall
- Feature Selection in Clustering Problems Volker Roth, 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, Yoram Singer, Christopher D. Manning
- Minimax Embeddings Matthew Brand
- No Unbiased Estimator of the Variance of K-Fold Cross-Validation Yoshua Bengio, Yves Grandvalet
- Bias-Corrected Bootstrap and Model Uncertainty Harald Steck, Tommi S. Jaakkola
- 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 A. Bilmes
- Classification with Hybrid Generative/Discriminative Models Rajat Raina, Yirong Shen, Andrew McCallum, Andrew Y. Ng
- A Model for Learning the Semantics of Pictures Victor Lavrenko, R. Manmatha, Jiwoon Jeon
- Algorithms for Interdependent Security Games Michael Kearns, Luis E. Ortiz
- 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 Hähnel, Christopher Baker, Zachary Omohundro, Carlos Reverte, Scott Thayer, Charles Whittaker, William Whittaker, Wolfram Burgard, Sebastian Thrun
- Semi-supervised Protein Classification Using Cluster Kernels Jason Weston, Denny Zhou, André Elisseeff, William S. Noble, Christina S. Leslie
- Statistical Debugging of Sampled Programs Alice X. Zheng, Michael I. Jordan, 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, António M. Baptista
- Modeling User Rating Profiles For Collaborative Filtering Benjamin M. 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, Andrew W. Moore
- Link Prediction in Relational Data Ben Taskar, Ming-fai Wong, Pieter Abbeel, Daphne Koller
- 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
- 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 Detect Cognitive States across Multiple Human 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. Meinertzhagen, 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 Müller
- Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron Sung C. Jun, Barak A. Pearlmutter
- Gaussian Processes in Reinforcement Learning Malte Kuss, Carl E. Rasmussen
- Applying Metric-Trees to Belief-Point POMDPs Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
- ARA*: Anytime A* with Provable Bounds on Sub-Optimality Maxim Likhachev, Geoffrey J. Gordon, Sebastian Thrun
- Approximate Planning in POMDPs with Macro-Actions Georgios Theocharous, Leslie P. Kaelbling
- Envelope-based Planning in Relational MDPs Natalia H. Gardiol, Leslie P. Kaelbling
- An MDP-Based Approach to Online Mechanism Design David C. Parkes, Satinder P. Singh
- Autonomous Helicopter Flight via Reinforcement Learning H. J. Kim, Michael I. Jordan, Shankar Sastry, Andrew Y. Ng
- All learning is Local: Multi-agent Learning in Global Reward Games Yu-han Chang, Tracey Ho, Leslie P. Kaelbling
- 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. A. Bagnell, Sham M. Kakade, Jeff G. Schneider, Andrew Y. Ng
- 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, Satinder P. Singh
- 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, Geoffrey J. Gordon, Sebastian Thrun
- Distributed Optimization in Adaptive Networks Ciamac C. Moallemi, Benjamin V. Roy
- Linear Program Approximations for Factored Continuous-State Markov Decision Processes Milos Hauskrecht, Branislav Kveton
- Insights from Machine Learning Applied to Human Visual Classification Felix A. Wichmann, Arnulf B. Graf
- Sensory Modality Segregation Virginia Sa
- Reasoning about Time and Knowledge in Neural Symbolic Learning Systems Artur 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 J. 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 Thomas L. Griffiths, Joshua B. Tenenbaum
- 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, Geoffrey J. Gordon, David S. Touretzky, Nathaniel D. Daw
- 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 A. Boahen
- A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural Systems Rock Z. Shi, Timothy K. 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, Alan F. Murray
- 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. A. Lewis
- A Neuromorphic Multi-chip Model of a Disparity Selective Complex Cell Bertram E. Shi, Eric K. Tsang
- 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, Ran El-Yaniv, Ron Meir
- Online Learning of Non-stationary Sequences Claire Monteleoni, Tommi S. Jaakkola
- On the Dynamics of Boosting Cynthia Rudin, Ingrid Daubechies, Robert E. 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, Olivier Bousquet
- 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 Tong Zhang
- Variational Linear Response Manfred Opper, Ole Winther
- Geometric Clustering Using the Information Bottleneck Method Susanne Still, William Bialek, Léon Bottou
- Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates Peter L. Bartlett, Michael I. Jordan, 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 Dörthe Malzahn, Manfred Opper
- Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks Justin Werfel, Xiaohui Xie, H. S. Seung
- Ambiguous Model Learning Made Unambiguous with 1/f Priors Gurinder S. Atwal, William Bialek
- Information Bottleneck for Gaussian Variables Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss
- Measure Based Regularization Olivier Bousquet, Olivier Chapelle, Matthias Hein
- Online Passive-Aggressive Algorithms Shai Shalev-shwartz, Koby Crammer, Ofer Dekel, Yoram Singer
- Margin Maximizing Loss Functions Saharon Rosset, Ji Zhu, Trevor J. Hastie
- The Doubly Balanced Network of Spiking Neurons: A Memory Model with High Capacity Yuval Aviel, David Horn, Moshe Abeles
- Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons Thomas Natschläger, 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 of Working Memory Aaron J. Gruber, Peter Dayan, Boris S. Gutkin, Sara A. Solla
- Circuit Optimization Predicts Dynamic Networks for Chemosensory Orientation in Nematode C. elegans Nathan A. Dunn, John S. Conery, Shawn R. Lockery
- A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning Maneesh Sahani
- Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron? Yoichi Miyawaki, Masato Okada
- Plasticity Kernels and Temporal Statistics Peter Dayan, Michael Häusser, Michael London
- Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model Liam Paninski, Eero P. Simoncelli, Jonathan W. Pillow
- Design of Experiments via Information Theory Liam Paninski
- Probabilistic Inference in Human Sensorimotor Processing Konrad P. Körding, Daniel M. Wolpert
- Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter Kazuyuki Samejima, Kenji Doya, Yasumasa Ueda, Minoru Kimura
- Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic Biophysics Bernd Porr, Ausra Saudargiene, Florentin Wörgötter
- 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 C. Kelly, Tai Sing Lee
- Prediction on Spike Data Using Kernel Algorithms Jan Eichhorn, Andreas Tolias, Alexander Zien, Malte Kuss, Jason Weston, Nikos Logothetis, Bernhard Schölkopf, Carl E. Rasmussen
- 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, Sam T. Roweis, Brendan J. Frey
- Eigenvoice Speaker Adaptation via Composite Kernel Principal Component Analysis 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
- Local Phase Coherence and the Perception of Blur Zhou Wang, Eero P. Simoncelli
- 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 Fang Fang, Daniel Kersten, Paul R. Schrater, Alan L. Yuille
- 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, Florentin Wörgötter
- Bounded Invariance and the Formation of Place Fields Reto Wyss, Paul F. Verschure
- Discriminating Deformable Shape Classes Salvador Ruiz-correa, Linda G. Shapiro, Marina Meila, Gabriel Berson
- Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes Kevin P. Murphy, Antonio Torralba, William T. Freeman
- Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence Amit Gruber, Yair Weiss
- 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 Facial Expression Classification G.C. Littlewort, M.S. Bartlett, I.R. Fasel, J. Chenu, T. Kanda, H. Ishiguro, J.R. Movellan
- Salient Boundary Detection using Ratio Contour Song Wang, Toshiro Kubota, Jeffrey M. Siskind
- Geometric Analysis of Constrained Curves Anuj Srivastava, Washington Mio, Xiuwen Liu, Eric Klassen
- A Sampled Texture Prior for Image Super-Resolution Lyndsey C. Pickup, Stephen J. Roberts, Andrew Zisserman
- Bayesian Color Constancy with Non-Gaussian Models Charles Rosenberg, Alok Ladsariya, Tom Minka
- An Improved Scheme for Detection and Labelling in Johansson Displays Claudio Fanti, Marzia Polito, Pietro Perona