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Conference Materials

Neural Information Processing Systems 2001 (NIPS 14)

	Sampling techniques for kernel methods Dimitris Achlioptas, Frank McSherry and Bernhard Schölkopf Geometrical singularities in the neuromanifold of multilayer perceptrons Shun-ichi Amari, Hyeyoung Park and Tomoko Ozeki Rao-Blackwellised particle filtering via data augmentation Christophe Andrieu, Nando Freitas and Arnaud Doucet Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion Giorgio Ascoli and Alexei Samsonovich Thin junction trees Francis Bach and Michael Jordan Perceptual metamers in stereoscopic vision Benjamin Backus Reinforcement learning with long short-term memory Bram Bakker The infinite hidden Markov model Matthew Beal, Zoubin Ghahramani and Carl Rasmussen Receptive field structure of flow detectors for heading perception Jaap Beintema, Albert Berg and Markus Lappe Laplacian eigenmaps and spectral techniques for embedding and clustering Mikhail Belkin and Partha Niyogi Duality, geometry, and Support Vector Regression Jinbo Bi and Kristin Bennett Intransitive likelihood-ratio classifiers Jeff Bilmes, Gang Ji and Marina Meil\u{a} Classifying Single Trial EEG: Towards Brain Computer Interfacing Benjamin Blankertz, Gabriel Curio and Klaus-Robert Müller Latent Dirichlet allocation David Blei, Andrew Ng and Michael Jordan Circuits for VLSI implementation of temporally-asymmetric Hebbian learning Adria Bofill, Alan Murray and Damon Thompson The noisy Euclidean traveling salesman problem and learning Mikio Braun and Joachim Buhmann Switch packet arbitration via queue-learning Timothy Brown Relative density nets: A new way to combime backpropogation with HMM's Andrew Brown and Geoffrey Hinton Orientational and geometric determinants of place and head-direction Neil Burgess and Tom Hartley Bayesian predictive profiles with applications to retail transaction data Igor Cadez and Padhraic Smyth A sequence kernel and its application to speaker recognition William Campbell Tempo tracking and rhythm quantization by Sequential Monte Carlo Ali Cemgil and Bert Kappen On the generalization ability of on-line learning algorithms Nicolò Cesa-Bianchi, Alex Conconi and Claudio Gentile Playing is believing: The role of beliefs in multi-agent learning Yu-Han Chang and Leslie Kaelbling Estimating car insurance premia: A case study in high-dimensional data inference Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi and Linyan Meng Incorporating invariances in nonlinear Support Vector Machines Olivier Chapelle and Bernhard Schölkopf Group redundancy measures reveal redundancy reduction in the auditory pathway Gal Chechik, Amir Globerson, Naftali Tishby, Michael Anderson, Eric Young and Israel Nelken A generalization of principal component analysis to the Exponential family Michael Collins, Sanjoy Dasgupta and Robert Schapire A parallel mixture of SVMs for very large scale problems Ronan Collobert, Samy Bengio and Yoshua Bengio A maximum-likelihood approach to modeling multisensory enhancement Hans Colonius and Adele Diederich The `g` Factor: Relating distributions on features to distributions on images James Coughlan and A. Yuille Modeling temporal structure in classical conditioning Aaron Courville and David Touretzky Pranking with ranking Koby Crammer and Yoram Singer Spectral kernel methods for clustering Nello Cristianini, John Shawe-Taylor and Jaz Kandola On kernel-target alignment Nello Cristianini, John Shawe-Taylor, Andre Elisseeff and Jaz Kandola TAP Gibbs free energy, belief propagation and sparsity Lehel Csató, Manfred Opper and Ole Winther Semi-supervised MarginBoost F. d'Alché-Buc, Yves Grandvalet and Christophe Ambroise Modularity in the motor system: Decomposition of muscle patterns as combinations of time-varying synergies Andrea d'Avella and Matthew Tresch PAC generalization bounds for co-training Sanjoy Dasgupta, Michael Littman and David McAllester ACh, uncertainty, and cortical inference Peter Dayan and Angela Yu Batch value function approximation via support vectors Thomas Dietterich and Xin Wang Adaptive nearest neighbor classification using Support Vector Machines Carlotta Domeniconi and Dimitrios Gunopulos Learning from infinite data in finite time Pedro Domingos and Geoff Hulten Linking motor learning to function approximation: Learning in an unlearnable force field Opher Donchin and Reza Shadmehr Probabilistic principles in unsupervised learning of visual structure: Human data and a model Shimon Edelman, Benjamin Hiles, Hwajin Yang and Nathan Intrator Exact differential equation population dynamics for Integrate-and-Fire neurons Julian Eggert and Berthold Bäuml Iterative double clustering for unsupervised and semi-supervised learning Ran El-Yaniv and Oren Souroujon A kernel method for multi-labelled classification André Elisseeff and Jason Weston Convergence of optimistic and incremental Q-learning Eyal Even-Dar and Yishay Mansour Approximate dynamic programming via linear programming Daniela Farias and Benjamin Roy Analysis of sparse Bayesian learning Anita Faul and Michael Tipping Adaptive sparseness using Jeffreys prior Mário Figueiredo Incremental learning and selective sampling via parametric optimization framework for SVM Shai Fine and Katya Scheinberg KLD-Sampling: Adaptive particle filters Dieter Fox Improvisation and learning Judy Franklin ALGONQUIN -- Learning dynamic noise models from noisy speech for robust speech recognition Brendan Frey, Trausti Kristjansson, Li Deng and Alex Acero Very loopy belief propagation for unwrapping phase images Brendan Frey, Ralf Koetter and Nemanja Petrovic Fast, large-scale transformation-invariant clustering Brendan Frey and Nebojsa Jojic Product analysis: Learning to model observations as products of hidden variables Brendan Frey, Anitha Kannan and Nebojsa Jojic Probabilistic Inference of Hand Motion from Neural Activity in Motor Context Y. Gao, M. Black, E. Bienenstock, S. Shoham and J. Donoghue Motivated reinforcement learning Peter Gatsby Stochastic mixed-signal VLSI architecture for high-dimensional kernel machines Roman Genov and Gert Cauwenberghs Discriminative direction for kernel classifiers Polina Golland Speech recognition with missing data using recurrent neural nets P. Green and S. Parveen Variance reduction techniques for gradient estimates in reinforcement learning Evan Greensmith, Peter Bartlett and Jonathan Baxter Using vocabulary knowledge in Bayesian multinomial estimation Thomas Griffiths and Joshua Tenenbaum Rates of convergence of performance gradient estimates using function approximation and bias in reinforcement learning Gregory Grudic and Lyle Ungar Multiagent planning with factored MDPs Carlos Guestrin, Daphne Koller and Ronald Parr Escaping the convex hull with Extrapolated Vector Machines Patrick Haffner A theory of neural integration in the head-direction system Richard Hahnloser, Xiaohui Xie and H. Seung Kernel feature spaces and nonlinear blind source separation Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe and Klaus-Robert Müller Categorization by learning and combining object parts Bernd Heisele, Thomas Serre, Massimiliano Pontil, Thomas Vetter and Tomaso Poggio Algorithmic luckiness Ralf Herbrich and Robert Williamson Audio-Visual sound separation via Hidden Markov Models John Hershey and Michael Casey The method of quantum clustering David Horn and Assaf Gottlieb Distribution of mutual information Marcus Hutter Information geometrical framework for analyzing belief propagation decoder Shiro Ikeda, Toshiyuki Tanaka and Shun-ichi Amari Modeling the modulatory effect of attention on human spatial vision Laurent Itti, Jochen Braun and Christof Koch Active information retrieval Tommi Jaakkola and Hava Siegelmann Fragment completion in humans and machines David Jacobs, Bas Rokers, Archisman Rudra and Zili Liu Cobot: A social reinforcement learning agent Charles Jr., Christian Shelton, Michael Kearns, Satinder Singh and Peter Stone A natural policy gradient Sham Kakade Novel iteration schemes for the Cluster Variation Method Hilbert Kappen and Wim Wiegerinck 3 state neurons for contextual processing Adam Kepecs and Sridhar Raghavachari Efficiency versus convergence of Boolean kernels for on-line learning algorithms Roni Khardon, Dan Roth and Rocco Servedio Online learning with kernels Jyrki Kivinen, Alex Smola and Robert Williamson Natural language grammar induction using a constituent-context model Dan Klein and Christopher Manning Small-world phenomena and the dynamics of information Jon Kleinberg Incremental A* S. Koenig and M. Likhachev A Dynamic HMM for on-line segmentation of sequential data Jens Kohlmorgen and Steven Lemm The emergence of multiple movement units in the presence of noise and feedback delay Michael Kositsky and Andrew Barto Kernel machines and Boolean functions Adam Kowalczyk, Alex Smola and Robert Williamson Model-free Least Squares Policy Iteration Michail Lagoudakis and Ronald Parr Minimax probability machine Gert Lanckriet, Laurent Ghaoui, Chiranjib Bhattacharyya and Michael Jordan (Not) Bounding the true error John Langford and Rich Caruana Associative memory in realistic neuronal networks P. Latham Optimising synchronisation times for mobile devices Neil Lawrence, Antony Rowstron, Christopher Bishop and Michael Taylor Boosting and Maximum Likelihood for Exponentional Models Guy Lebanon and John Lafferty Means, correlations and bounds M. Leisink and H. Kappen Predictive representations of state Michael Littman, Richard Sutton and Satinder Singh An efficient, exact algorithm for solving tree-structured graphical games Michael Littman, Michael Kearns and Satinder Singh Orientation-selective aVLSI spiking neurons Shih-Chii Liu, Jörg Kramer, Giacomo Indiveri, Tobias Delbrück and Rodney Douglas A variational approach to learning curves Dörthe Malzahn and Manfred Opper The steering approach for multi-criteria reinforcement learning Shie Mannor and Nahum Shimkin Self-regulation mechanism of temporally asymmetric Hebbian plasticity Narihisa Matsumoto and Masato Okada Convolution kernels for natural language mcollins@research.att.com mcollins@research.att.com and Nigel Duffy Estimating the reliability of ICA projections F. Meinecke, A. Ziehe, M. Kawanabe and K.-R. M\"uller Quantizing density estimators Peter Meinicke and Helge Ritter An efficient clustering algorithm using stochastic association model and its implementation using nanostructures Takashi Morie, Tomohiro Matsuura, Makoto Nagata and Atsushi Iwata Prodding the ROC Curve: Constrained optimization of classifier performance Michael Mozer, Robert Dodier, Michael Colagrosso, C\'esar Guerra-Salcedo and Richard Wolniewicz A rational analysis of cognitive control in a speeded discrimination task Michael Mozer, Michael Colagrosso and David Huber Efficient resources allocation for Markov Decision Processes Rémi Munos Linear time inference in hierarchical HMMs Kevin Murphy and Mark Paskin Information-geometric decomposition in spike analysis Hiroyuki Nakahara and Shun-ichi Amari A Bayesian model predicts human parse preference and reading times in sentence processing Srini Narayanan and Daniel Jurafsky Grammar transfer in a second order recurrent neural network Michiro Negishi and Stephen Hanson Entropy and inference, revisited Ilya Nemenman, Fariel Shafee and William Bialek On spectral clustering: Analysis and an algorithm Andrew Ng, Michael Jordan and Yair Weiss On discriminative vs. generative classifiers: A comparison of logistic regression and naive Bayes Andrew Ng and Michael Jordan A model of the phonological loop: Generalization and binding Randall O'Reilly and Rodolfo Soto Generalizable relational binding from coarse-coded distributed representations Randall O'Reilly and Richard Busby Hyperbolic self-organizing maps for semantic navigation Jörg Ontrup and Helge Ritter Asymptotic universality for learning curves of Support Vector Machines M. Opper and R. Urbanczik Learning hierarchical structures with Linear Relational Embedding Alberto Paccanaro and Geoffrey Hinton Grammatical bigrams Mark Paskin Matching free trees with replicator equations Marcello Pelill Learning a Gaussian process prior for automatically generating music playlists John Platt, Christopher Burges, Steven Swenson, Christopher Weare and Alice Zheng Grouping and dimensionality reduction by locally linear embedding Marzia Polito and Pietro Perona MIME: Mutual information minimization and entropy maximization for Bayesian belief propagation Anand Rangarajan and Alan Yuille A Bayesian network for real-time musical accompaniment Christopher Raphael Infinite mixtures of Gaussian process experts Carl Rasmussen and Zoubin Ghahramani On the convergence of leveraging Gunnar Rätsch, Sebastian Mikaz and Manfred Warmuth Scaling laws and local minima in Hebbian ICA Magnus Rattray and Gleb Basalyga Causal categorization with Bayes nets Bob Rehder The intelligent surfer: Probabilistic combination of link and content information in PageRank Matthew Richardson and Pedro Domingos Learning body pose via specialized maps Rómer Rosales and Stan Sclaroff Global coordination of local linear models Sam Roweis, Lawrence Saul and Geoffrey Hinton Eye movements and the maturation of cortical orientation selectivity Michel Rucci and Antonino Casile Constructing distributed representations using additive clustering Wheeler Ruml A hierarchical model of complex cells in visual cortex for the binocular perception of motion-in-depth Silvio Sabatini, Fabio Solari, Giulia Andreani, Chiara Bartolozzi and Giacomo Bisio The fidelity of local ordinal encoding Javid Sadr, Sayan Mukherjee, Keith Thoresz and Pawan Sinha Multiplicative updates for classification by mixture models Lawrence Saul and Daniel Leey Computing time lower bounds for recurrent sigmoidal neural networks Michael Schmitt Direct value-approximation for factored MDPs Dale Schuurmans and Relu Patrascu Characterizing neural gain control using spike-triggered covariance Odelia Schwartz, E. Chichilnisky and Eero Simoncelli Covariance kernels from Bayesian generative models Matthias Seeger Probabilistic abstraction hierarchies Eran Segal, Daphne Koller and Dirk Ormoneit Correlation codes in neuronal populations Maoz Shamir and Haim Sompolinsky Reinforcement Learning and Time Perception -- a Model of Animal Experiments J. Shapiro and John Wearden On the concentration of spectral properties John Shawe-Taylor, Nello Cristianini and Jaz Kandola Dynamic time-alignment kernel in Support Vector Machine Hiroshi Shimodaira, Ken-ichi Noma, Mitsuru Nakai and Shigeki Sagayama Learning spike-based correlations and conditional probabilities in silicon Aaron Shon, David Hsu and Chris Diorio Agglomerative multivariate information bottleneck Noam Slonim, Nir Friedman and Naftali Tishby Speech recognition using SVMs Nathan Smith and Mark Gales Gaussian process regression with mismatched models Peter Sollich Unsupervised learning of human motion models Yang Song, Luis Goncalves and Pietro Perona Transform-invariant image decomposition with similarity templates Chris Stauffer, Erik Miller and Kinh Tieu Bayesian time series classification Peter Sykacek and Stephen Roberts Partially labeled classification with Markov random walks Martin Szummer and Tommi Jaakkola Information-geometrical significance of sparsity in Gallager codes Toshiyuki Tanaka, Shiro Ikeda and Shun-ichi Amari Why neuronal dynamics should control synaptic learning rules Jesper Tegnér and Ádám Kepecs The unified propagation and scaling algorithm Yee Teh and Max Welling Risk sensitive particle filters Sebastian Thrun, John Langford and Vandi Verma Learning discriminative feature transforms to low dimensions in low dimensions Kari Torkkola Contextual modulation of target saliency Antonio Torralba Effective size of receptive fields of inferior temporal visual cortex neurons in natural scenes Thomas Trappenberg, Edmund Rolls and Simon Stringer A new discriminative kernel from probabilistic models K. Tsuda, M. Kawanabe, G. Rätsch, S. Sonnenburg and K.-R. üller K-Local hyperplane and convex distance Nearest Neighbor algorithms Pascal Vincent and Yoshua Bengio Fast and robust classification using asymmetric AdaBoost and a detector cascade Paul Viola and Michael Jones Multi dimensional ICA to separate correlated sources Roland Vollgraf and Klaus Obermayer Tree-based reparameterization for approximate inference on loopy graphs Martin Wainwright, Tommi Jaakkola and Alan Willsky Stabilizing value function approximation with the BFBP algorithm Xin Wang and Thomas Dietterich Active learning in the drug discovery process Manfred Warmuth, Gunnar Rätsch, Michael Mathieson, Jun Liao and Christian Lemmenz Activity driven adaptive stochastic resonance Gregor Wenning and Klaus Obermayer Learning lateral interactions for feature binding and sensory segmentation Heiko Wersing A rotation and translation invariant discrete saliency network Lance Williams and John Zweck Products of Gaussians Christopher Williams, Felix Agakov and Stephen Felderhof Fast parameter estimation using Green's functions K. Wong and Fuli Li Spike timing and the coding of naturalistic sounds in a central auditory area of songbirds Brian Wright, Kamal Sen, William Bialek and Allison Doupe A neural oscillator model of auditory selective attention Stuart Wrigley and Guy Brown Neural implementation of Bayesian inference in population codes Si Wu and Shun-ichi Amari Generating velocity tuning by asymmetric recurrent connections Xiaohui Xie and Martin Giese Analog soft-pattern-matching classifier using floating-gate MOS Technology Toshihiko yamasaki and Tadashi Shibata Face recognition using kernel methods Ming-Hsuan Yang Sequential noise compensation by sequential Monte Carlo method Kaisheng Yao and Satoshi Nakamura A quantitative model of counterfactual reasoning Daniel Yarlet and Michael Ramscar Grouping with bias Stella Yu and Jianbo Shi The Concave-Convex procedure (CCCP) A. Yuille and Anand Rangarajan Reducing multiclass to binary by coupling probability estimates Bianca Zadrozny Spectral relaxation for K-means clustering Hongyuan Zha, Xiaofeng He, Chris Ding, Horst Simon and Ming Gu EM-DD: An improved multiple-instance learning technique Qi Zhang and Sally Goldman Generalization performance of some learning problems in Hilbert functional spaces Tong Zhang A general greedy approximation algorithm with applications Tong Zhang Kernel logistic regression and the import vector machine Ji Zhu and Trevor Hastie Blind source separation via multinode sparse representation Michael Zibulevsky, Pavel Kisilev, Yehoshua Zeevi and Barak Pearlmutter Active portfolio-management based on error correction neural networks Hans Zimmermann, Ralph Neuneier and Ralph Grothmann

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