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All publications in 2005
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Large margin non-linear embedding
Alexander Zien and Joaquin Q. Candela
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


2D Conditional Random Fields for Web information extraction
Jun Zhu, Zaiqing Nie, Ji-rong Wen, Bo Zhang and Wei-ying Ma
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Xiaojin Zhu and John D. Lafferty
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A new Mallows distance based metric for comparing clusterings
Ding Zhou, Jia Li and Hongyuan Zha
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning from labeled and unlabeled data on a directed graph
Dengyong Zhou, Jiayuan Huang and Bernhard Schölkopf
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Augmenting naive Bayes for ranking
Harry Zhang, Liangxiao Jiang and Jiang Su
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning Gaussian processes from multiple tasks
Kai Yu, Volker Tresp and Anton Schwaighofer
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Dirichlet enhanced relational learning
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu and Hans-peter Kriegel
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Building Sparse Large Margin Classifiers
Mingrui Wu, Bernhard Schölkopf and Gökhan H. Bakir
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Linear Asymmetric Classifier for cascade detectors
Jianxin Wu, Matthew D. Mullin and James M. Rehg
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning predictive state representations in dynamical systems without reset
Britton Wolfe, Michael R. James and Satinder P. Singh
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Incomplete-data classification using logistic regression
David Williams, Xuejun Liao, Ya Xue and Lawrence Carin
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning predictive representations from a history
Eric Wiewiora
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans and Li Cheng
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


New kernels for protein structural motif discovery and function classification
Chang Wang and Stephen D. Scott
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Bayesian sparse sampling for on-line reward optimization
Tao Wang, Daniel J. Lizotte, Michael H. Bowling and Dale Schuurmans
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Implicit surface modelling as an eigenvalue problem
Christian Walder, Olivier Chapelle and Bernhard Schölkopf
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Hierarchical Dirichlet model for document classification
Sriharsha Veeramachaneni, Diego Sona and Paolo Avesani
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Propagating distributions on a hypergraph by dual information regularization
Koji Tsuda
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Core Vector Regression for very large regression problems
Ivor W. Tsang, James T. Kwok and Kimo T. Lai
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning discontinuities with products-of-sigmoids for switching between local models
Marc Toussaint and Sethu Vijayakumar
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Multimodal oriented discriminant analysis
Fernando Torre and Takeo Kanade
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning structured prediction models: a large margin approach
Vassil Chatalbashev, Daphne Koller, Carlos Guestrin and Ben Taskar
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


TD(lambda) networks: temporal-difference networks with eligibility traces
Brian Tanner and Richard S. Sutton
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Finite time bounds for sampling based fitted value iteration
Csaba Szepesvári and Rémi Munos
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Unifying the error-correcting and output-code AdaBoost within the margin framework
Yijun Sun, Sinisa Todorovic, Jian Li and Dapeng Wu
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning
Qiang Sun and Gerald Dejong
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A theoretical analysis of Model-Based Interval Estimation
Alexander L. Strehl and Michael L. Littman
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Large scale genomic sequence SVM classifiers
Sören Sonnenburg, Gunnar Rätsch and Bernhard Schölkopf
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Compact approximations to Bayesian predictive distributions
Edward Snelson and Zoubin Ghahramani
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Active learning for sampling in time-series experiments with application to gene expression analysis
Rohit Singh, Nathan Palmer, David K. Gifford, Bonnie Berger and Ziv Bar-joseph
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Beyond the point cloud: from transductive to semi-supervised learning
Vikas Sindhwani, Partha Niyogi and Mikhail Belkin
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Identifying useful subgoals in reinforcement learning by local graph partitioning
Özgür Simsek, Alicia P. Wolfe and Andrew G. Barto
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


New d-separation identification results for learning continuous latent variable models
Ricardo Silva and Richard Scheines
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Fast inference and learning in large-state-space HMMs
Sajid M. Siddiqi and Andrew W. Moore
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Non-negative tensor factorization with applications to statistics and computer vision
Amnon Shashua and Tamir Hazan
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Analysis and extension of spectral methods for nonlinear dimensionality reduction
Fei Sha and Lawrence K. Saul
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Object correspondence as a machine learning problem
Bernhard Schölkopf, Florian Steinke and Volker Blanz
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Expectation maximization algorithms for conditional likelihoods
Jarkko Salojärvi, Kai Puolamäki and Samuel Kaski
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Supervised dimensionality reduction using mixture models
Sajama Sajama and Alon Orlitsky
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Estimating and computing density based distance metrics
Sajama Sajama and Alon Orlitsky
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning hierarchical multi-category text classification models
Juho Rousu, Craig Saunders, Sándor Szedmák and John Shawe-taylor
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Integer linear programming inference for conditional random fields
Dan Roth and Wen-tau Yih
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Why skewing works: learning difficult Boolean functions with greedy tree learners
Bernard Rosell, Lisa Hellerstein, Soumya Ray and David Page
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Coarticulation: an approach for generating concurrent plans in Markov decision processes
Khashayar Rohanimanesh and Sridhar Mahadevan
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Fast maximum margin matrix factorization for collaborative prediction
Jason Rennie and Nathan Srebro
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Generalized skewing for functions with continuous and nominal attributes
Soumya Ray and David Page
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Supervised versus multiple instance learning: an empirical comparison
Soumya Ray and Mark Craven
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Healing the relevance vector machine through augmentation
Carl E. Rasmussen and Joaquin Q. Candela
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A model for handling approximate, noisy or incomplete labeling in text classification
Ganesh Ramakrishnan, Krishna P. Chitrapura, Raghu Krishnapuram and Pushpak Bhattacharyya
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Independent subspace analysis using geodesic spanning trees
Barnabás Póczos and András Lörincz
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Optimizing abstaining classifiers using ROC analysis
Tadeusz Pietraszek
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Discriminative versus generative parameter and structure learning of Bayesian network classifiers
Franz Pernkopf and Jeff A. Bilmes
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Q-learning of sequential attention for visual object recognition from informative local descriptors
Lucas Paletta, Gerald Fritz and Christin Seifert
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A graphical model for chord progressions embedded in a psychoacoustic space
Jean-françcois Paiement, Douglas Eck, Samy Bengio and David Barber
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Recycling data for multi-agent learning
Santiago Ontañón and Enric Plaza
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Predicting good probabilities with supervised learning
Alexandru Niculescu-mizil and Rich Caruana
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


An efficient method for simplifying support vector machines
Ducdung Nguyen and Tu B. Ho
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning first-order probabilistic models with combining rules
Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern and Angelo C. Restificar
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Dynamic preferences in multi-criteria reinforcement learning
Sriraam Natarajan and Prasad Tadepalli
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


High speed obstacle avoidance using monocular vision and reinforcement learning
Jeff Michels, Ashutosh Saxena and Andrew Y. Ng
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Weighted decomposition kernels
Sauro Menchetti, Fabrizio Costa and Paolo Frasconi
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Comparing clusterings: an axiomatic view
Marina Meila
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees
H. B. Mcmahan, Maxim Likhachev and Geoffrey J. Gordon
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


The cross entropy method for classification
Shie Mannor, Dori Peleg and Reuven Y. Rubinstein
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Proto-value functions: developmental reinforcement learning
Sridhar Mahadevan
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Modeling word burstiness using the Dirichlet distribution
Rasmus E. Madsen, David Kauchak and Charles Elkan
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


ROC confidence bands: an empirical evaluation
Sofus A. Macskassy, Foster J. Provost and Saharon Rosset
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Naive Bayes models for probability estimation
Daniel Lowd and Pedro Domingos
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Unsupervised evidence integration
Philip M. Long, Vinay Varadan, Sarah Gilman, Mark Treshock and Rocco A. Servedio
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Predicting protein folds with structural repeats using a chain graph model
Yan Liu, Eric P. Xing and Jaime G. Carbonell
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Logistic regression with an auxiliary data source
Xuejun Liao, Ya Xue and Lawrence Carin
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Predicting relative performance of classifiers from samples
Rui Leite and Pavel Brazdil
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Heteroscedastic Gaussian process regression
Quoc V. Le, Stéphane Canu and Alex J. Smola
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


PAC-Bayes risk bounds for sample-compressed Gibbs classifiers
Françcois Laviolette and Mario Marchand
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Relating reinforcement learning performance to classification performance
John Langford and Bianca Zadrozny
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A brain computer interface with online feedback based on magnetoencephalography
Thomas N. Lal, Michael Schröder, N. J. Hill, Hubert Preissl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer and Bernhard Schölkopf
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Semi-supervised graph clustering: a kernel approach
Brian Kulis, Sugato Basu, Inderjit S. Dhillon and Raymond J. Mooney
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Using additive expert ensembles to cope with concept drift
Jeremy Z. Kolter and Marcus A. Maloof
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning the structure of Markov logic networks
Stanley Kok and Pedro Domingos
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Computational aspects of Bayesian partition models
Mikko Koivisto and Kismat Sood
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Ensembles of biased classifiers
Rinat Khoussainov, Andreas Hess and Nicholas Kushmerick
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Generalized LARS as an effective feature selection tool for text classification with SVMs
S. S. Keerthi
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A comparison of tight generalization error bounds
Matti Kääriäinen and John Langford
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A causal approach to hierarchical decomposition of factored MDPs
Anders Jonsson and Andrew G. Barto
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Interactive learning of mappings from visual percepts to actions
Sébastien Jodogne and Justus H. Piater
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Error bounds for correlation clustering
Thorsten Joachims and John E. Hopcroft
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A support vector method for multivariate performance measures
Thorsten Joachims
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
Yushi Jing, Vladimir Pavlovic and James M. Rehg
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A smoothed boosting algorithm using probabilistic output codes
Rong Jin and Jian Zhang
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learn to weight terms in information retrieval using category information
Rong Jin, Joyce Y. Chai and Luo Si
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Evaluating machine learning for information extraction
Neil Ireson, Fabio Ciravegna, Mary E. Califf, Dayne Freitag, Nicholas Kushmerick and Alberto Lavelli
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning approximate preconditions for methods in hierarchical plans
Okhtay Ilghami, Héctor Muñoz-avila, Dana S. Nau and David W. Aha
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Multi-class protein fold recognition using adaptive codes
Eugene Ie, Jason Weston, William S. Noble and Christina S. Leslie
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A martingale framework for concept change detection in time-varying data streams
Shen-shyang Ho
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Adapting two-class support vector classification methods to many class problems
Simon I. Hill and Arnaud Doucet
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Online learning over graphs
Mark Herbster, Massimiliano Pontil and Lisa Wainer
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Bayesian hierarchical clustering
Katherine A. Heller and Zoubin Ghahramani
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Intrinsic dimensionality estimation of submanifolds in R$^{\mbox{d}}$
Matthias Hein and Jean-yves Audibert
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Statistical and computational analysis of locality preserving projection
Xiaofei He, Deng Cai and Wanli Min
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Robust one-class clustering using hybrid global and local search
Gunjan Gupta and Joydeep Ghosh
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Near-optimal sensor placements in Gaussian processes
Carlos Guestrin, Andreas Krause and Ajit P. Singh
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning strategies for story comprehension: a reinforcement learning approach
Eugene Grois and David C. Wilkins
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Online feature selection for pixel classification
Karen A. Glocer, Damian Eads and James Theiler
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Hierarchic Bayesian models for kernel learning
Mark Girolami and Simon Rogers
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Closed-form dual perturb and combine for tree-based models
Pierre Geurts and Louis Wehenkel
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Optimal assignment kernels for attributed molecular graphs
Holger Fröhlich, Jörg K. Wegner, Florian Sieker and Andreas Zell
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Supervised clustering with support vector machines
Thomas Finley and Thorsten Joachims
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Experimental comparison between bagging and Monte Carlo ensemble classification
Roberto Esposito and Lorenza Saitta
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Reinforcement learning with Gaussian processes
Yaakov Engel, Shie Mannor and Ron Meir
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Combining model-based and instance-based learning for first order regression
Kurt Driessens and Saso Dzeroski
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A practical generalization of Fourier-based learning
Adam Drake and Dan Ventura
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning as search optimization: approximate large margin methods for structured prediction
Daniel Marcu and Hal Daume
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning to compete, compromise, and cooperate in repeated general-sum games
Jacob W. Crandall and Michael A. Goodrich
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


A general regression technique for learning transductions
Corinna Cortes, Mehryar Mohri and Jason Weston
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


New approaches to support vector ordinal regression
Wei Chu and S. S. Keerthi
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Preference learning with Gaussian processes
Wei Chu and Zoubin Ghahramani
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Variational Bayesian image modelling
Li Cheng, Feng Jiao, Dale Schuurmans and Shaojun Wang
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Hedged learning: regret-minimization with learning experts
Yu-han Chang and Leslie P. Kaelbling
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Predicting probability distributions for surf height using an ensemble of mixture density networks
Michael Carney, Padraig Cunningham, Jim Dowling and Ciaran Lee
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM
Sylvain Calinon and Aude Billard
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning to rank using gradient descent
Christopher Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton and Gregory N. Hullender
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Learning class-discriminative dynamic Bayesian networks
John Burge and Terran Lane
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Reducing overfitting in process model induction
Will Bridewell, Narges B. Asadi, Pat Langley and Ljupco Todorovski
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Clustering through ranking on manifolds
Markus Breitenbach and Gregory Z. Grudic
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Action respecting embedding
Michael H. Bowling, Ali Ghodsi and Dana F. Wilkinson
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Multi-instance tree learning
Hendrik Blockeel, David Page and Ashwin Srinivasan
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Error limiting reductions between classification tasks
Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford and Bianca Zadrozny
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Multi-way distributional clustering via pairwise interactions
Ron Bekkerman, Ran El-yaniv and Andrew Mccallum
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Predictive low-rank decomposition for kernel methods
Francis R. Bach and Michael I. Jordan
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Fast condensed nearest neighbor rule
Fabrizio Angiulli
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Tempering for Bayesian C{\&}RT
Nicos Angelopoulos and James Cussens
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Active learning for Hidden Markov Models: objective functions and algorithms
Brigham Anderson and Andrew Moore
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Exploration and apprenticeship learning in reinforcement learning
Pieter Abbeel and Andrew Y. Ng
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Change Point Problems in Linear Dynamical Systems
Onno Zoeter and Tom Heskes
Journal of Machine Learning Research, 2005


Characterization of a Family of Algorithms for Generalized Discriminant Analysis on Undersampled Problems
Jieping Ye
Journal of Machine Learning Research, 2005


What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks
Weng-keen Wong, Andrew W. Moore, Gregory F. Cooper and Michael M. Wagner
Journal of Machine Learning Research, 2005


Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach
Lior Wolf and Amnon Shashua
Journal of Machine Learning Research, 2005


Variational Message Passing
John M. Winn and Christopher M. Bishop
Journal of Machine Learning Research, 2005


Prioritization Methods for Accelerating MDP Solvers
David Wingate and Kevin D. Seppi
Journal of Machine Learning Research, 2005


Learning from Examples as an Inverse Problem
Ernesto D. Vito, Lorenzo Rosasco, Andrea Caponnetto, Umberto D. Giovannini and Francesca Odone
Journal of Machine Learning Research, 2005


Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection
Koji Tsuda, Gunnar Rätsch and Manfred K. Warmuth
Journal of Machine Learning Research, 2005


Large Margin Methods for Structured and Interdependent Output Variables
Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann and Yasemin Altun
Journal of Machine Learning Research, 2005


Core Vector Machines: Fast SVM Training on Very Large Data Sets
Ivor W. Tsang, James T. Kwok and Pak-ming Cheung
Journal of Machine Learning Research, 2005


A Classification Framework for Anomaly Detection
Ingo Steinwart, Don R. Hush and Clint Scovel
Journal of Machine Learning Research, 2005


Combining Information Extraction Systems Using Voting and Stacked Generalization
Georgios Sigletos, Georgios Paliouras, Constantine D. Spyropoulos and Michael Hatzopoulos
Journal of Machine Learning Research, 2005


An MDP-Based Recommender System
Guy Shani, David Heckerman and Ronen I. Brafman
Journal of Machine Learning Research, 2005


Learning Module Networks
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller and Nir Friedman
Journal of Machine Learning Research, 2005


Denoising Source Separation
Jaakko Särelä and Harri Valpola
Journal of Machine Learning Research, 2005


Asymptotic Model Selection for Naive Bayesian Networks
Dmitry Rusakov and Dan Geiger
Journal of Machine Learning Research, 2005


Efficient Computation of Gapped Substring Kernels on Large Alphabets
Juho Rousu and John Shawe-taylor
Journal of Machine Learning Research, 2005


Efficient Margin Maximizing with Boosting
Gunnar Rätsch and Manfred K. Warmuth
Journal of Machine Learning Research, 2005


Frames, Reproducing Kernels, Regularization and Learning
Alain Rakotomamonjy and Stéphane Canu
Journal of Machine Learning Research, 2005


Expectation Consistent Approximate Inference
Manfred Opper and Ole Winther
Journal of Machine Learning Research, 2005


Learning the Kernel with Hyperkernels
Cheng S. Ong, Robert C. Williamson and Alex J. Smola
Journal of Machine Learning Research, 2005


Inner Product Spaces for Bayesian Networks
Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt and Hans-ulrich Simon
Journal of Machine Learning Research, 2005


Large scale networks fingerprinting and visualization using the k-core decomposition
J. I. Alvarez-hamelin, Luca Dall'asta, Alain Barrat and Alessandro Vespignani
Advances in Neural Information Processing Systems 18, 2005


Gradient Flow Independent Component Analysis in Micropower VLSI
Abdullah Celik, Milutin Stanacevic and Gert Cauwenberghs
Advances in Neural Information Processing Systems 18, 2005


An Approximate Inference Approach for the PCA Reconstruction Error
Manfred Opper
Advances in Neural Information Processing Systems 18, 2005


Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation
Jin Yu, Douglas Aberdeen and Nicol N. Schraudolph
Advances in Neural Information Processing Systems 18, 2005


Prediction and Change Detection
Mark Steyvers and Scott Brown
Advances in Neural Information Processing Systems 18, 2005


Learning vehicular dynamics, with application to modeling helicopters
Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng
Advances in Neural Information Processing Systems 18, 2005


Bayesian models of human action understanding
Chris Baker, Rebecca Saxe and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 18, 2005


Extracting Dynamical Structure Embedded in Neural Activity
Byron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu and Krishna V. Shenoy
Advances in Neural Information Processing Systems 18, 2005


Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators
Boaz Nadler, Stephane Lafon, Ioannis Kevrekidis and Ronald R. Coifman
Advances in Neural Information Processing Systems 18, 2005


Combining Graph Laplacians for Semi--Supervised Learning
Andreas Argyriou, Mark Herbster and Massimiliano Pontil
Advances in Neural Information Processing Systems 18, 2005


Saliency Based on Information Maximization
Neil Bruce and John Tsotsos
Advances in Neural Information Processing Systems 18, 2005


Variational EM Algorithms for Non-Gaussian Latent Variable Models
Jason Palmer, Kenneth Kreutz-delgado, Bhaskar D. Rao and David P. Wipf
Advances in Neural Information Processing Systems 18, 2005


Describing Visual Scenes using Transformed Dirichlet Processes
Antonio Torralba, Alan S. Willsky, Erik B. Sudderth and William T. Freeman
Advances in Neural Information Processing Systems 18, 2005


Off-policy Learning with Options and Recognizers
Doina Precup, Cosmin Paduraru, Anna Koop, Richard S. Sutton and Satinder P. Singh
Advances in Neural Information Processing Systems 18, 2005


Correlated Topic Models
John D. Lafferty and David M. Blei
Advances in Neural Information Processing Systems 18, 2005


Location-based activity recognition
Lin Liao, Dieter Fox and Henry Kautz
Advances in Neural Information Processing Systems 18, 2005


Fast Krylov Methods for N-Body Learning
Nando D. Freitas, Yang Wang, Maryam Mahdaviani and Dustin Lang
Advances in Neural Information Processing Systems 18, 2005


An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Architecture
Yusuke Nakashita, Yoshio Mita and Tadashi Shibata
Advances in Neural Information Processing Systems 18, 2005


Using ``epitomes'' to model genetic diversity: Rational design of HIV vaccine cocktails
Nebojsa Jojic, Vladimir Jojic, Christopher Meek, David Heckerman and Brendan J. Frey
Advances in Neural Information Processing Systems 18, 2005


Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods
Yaakov Engel, Peter Szabo and Dmitry Volkinshtein
Advances in Neural Information Processing Systems 18, 2005


Off-Road Obstacle Avoidance through End-to-End Learning
Urs Muller, Jan Ben, Eric Cosatto, Beat Flepp and Yann L. Cun
Advances in Neural Information Processing Systems 18, 2005


A Theoretical Analysis of Robust Coding over Noisy Overcomplete Channels
Eizaburo Doi, Doru C. Balcan and Michael S. Lewicki
Advances in Neural Information Processing Systems 18, 2005


Cue Integration for Figure/Ground Labeling
Xiaofeng Ren, Jitendra Malik and Charless C. Fowlkes
Advances in Neural Information Processing Systems 18, 2005


From Weighted Classification to Policy Search
Doron Blatt and Alfred O. Hero
Advances in Neural Information Processing Systems 18, 2005


Maximum Margin Semi-Supervised Learning for Structured Variables
Yasemin Altun, Mikhail Belkin and David A. Mcallester
Advances in Neural Information Processing Systems 18, 2005


The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search
Gregory Zelinsky, Wei Zhang, Bing Yu, Xin Chen and Dimitris Samaras
Advances in Neural Information Processing Systems 18, 2005


Nested sampling for Potts models
Iain Murray, David Mackay, Zoubin Ghahramani and John Skilling
Advances in Neural Information Processing Systems 18, 2005


Identifying Distributed Object Representations in Human Extrastriate Visual Cortex
Rory Sayres, David Ress and Kalanit Grill-spector
Advances in Neural Information Processing Systems 18, 2005


An Application of Markov Random Fields to Range Sensing
James Diebel and Sebastian Thrun
Advances in Neural Information Processing Systems 18, 2005


Preconditioner Approximations for Probabilistic Graphical Models
John D. Lafferty and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 18, 2005


Fast Gaussian Process Regression using KD-Trees
Yirong Shen, Matthias Seeger and Andrew Y. Ng
Advances in Neural Information Processing Systems 18, 2005


Learning Depth from Single Monocular Images
Ashutosh Saxena, Sung H. Chung and Andrew Y. Ng
Advances in Neural Information Processing Systems 18, 2005


Measuring Shared Information and Coordinated Activity in Neuronal Networks
Kristina Klinkner, Cosma Shalizi and Marcelo Camperi
Advances in Neural Information Processing Systems 18, 2005


Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity
Kenneth Hild, Kensuke Sekihara, Hagai T. Attias and Srikantan S. Nagarajan
Advances in Neural Information Processing Systems 18, 2005


Active Bidirectional Coupling in a Cochlear Chip
Bo Wen and Kwabena A. Boahen
Advances in Neural Information Processing Systems 18, 2005


Gaussian Processes for Multiuser Detection in CDMA receivers
Juan J. Murillo-fuentes, Sebastian Caro and Fernando Pérez-cruz
Advances in Neural Information Processing Systems 18, 2005


Goal-Based Imitation as Probabilistic Inference over Graphical Models
Deepak Verma and Rajesh P. Rao
Advances in Neural Information Processing Systems 18, 2005


On Local Rewards and Scaling Distributed Reinforcement Learning
Drew Bagnell and Andrew Y. Ng
Advances in Neural Information Processing Systems 18, 2005


Q-Clustering
Mukund Narasimhan, Nebojsa Jojic and Jeff A. Bilmes
Advances in Neural Information Processing Systems 18, 2005


Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
Jo-anne Ting, Aaron D'souza, Kenji Yamamoto, Toshinori Yoshioka, Donna Hoffman, Shinji Kakei, Lauren Sergio, John Kalaska and Mitsuo Kawato
Advances in Neural Information Processing Systems 18, 2005


Robust design of biological experiments
Patrick Flaherty, Adam Arkin and Michael I. Jordan
Advances in Neural Information Processing Systems 18, 2005


Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches
Anna Levina and Michael Herrmann
Advances in Neural Information Processing Systems 18, 2005


From Lasso regression to Feature vector machine
Fan Li, Yiming Yang and Eric P. Xing
Advances in Neural Information Processing Systems 18, 2005


Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms
Baback Moghaddam, Yair Weiss and Shai Avidan
Advances in Neural Information Processing Systems 18, 2005


Query by Committee Made Real
Ran Gilad-bachrach, Amir Navot and Naftali Tishby
Advances in Neural Information Processing Systems 18, 2005


Selecting Landmark Points for Sparse Manifold Learning
Jorge Silva, Jorge Marques and João Lemos
Advances in Neural Information Processing Systems 18, 2005


Generalization error bounds for classifiers trained with interdependent data
Nicolas Usunier, Massih-reza Amini and Patrick Gallinari
Advances in Neural Information Processing Systems 18, 2005


Soft Clustering on Graphs
Kai Yu, Shipeng Yu and Volker Tresp
Advances in Neural Information Processing Systems 18, 2005


Is Early Vision Optimized for Extracting Higher-order Dependencies?
Yan Karklin and Michael S. Lewicki
Advances in Neural Information Processing Systems 18, 2005


Online Discovery and Learning of Predictive State Representations
Peter Mccracken and Michael Bowling
Advances in Neural Information Processing Systems 18, 2005


Faster Rates in Regression via Active Learning
Rebecca Willett, Robert Nowak and Rui M. Castro
Advances in Neural Information Processing Systems 18, 2005


Beyond Gaussian Processes: On the Distributions of Infinite Networks
Ricky Der and Daniel D. Lee
Advances in Neural Information Processing Systems 18, 2005


Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care
Christopher Williams, John Quinn and Neil Mcintosh
Advances in Neural Information Processing Systems 18, 2005


Modeling Neural Population Spiking Activity with Gibbs Distributions
Frank Wood, Stefan Roth and Michael J. Black
Advances in Neural Information Processing Systems 18, 2005


Multiple Instance Boosting for Object Detection
Cha Zhang, John C. Platt and Paul A. Viola
Advances in Neural Information Processing Systems 18, 2005


Consistency of one-class SVM and related algorithms
Régis Vert and Jean-philippe Vert
Advances in Neural Information Processing Systems 18, 2005


Scaling Laws in Natural Scenes and the Inference of 3D Shape
Tai-sing Lee and Brian R. Potetz
Advances in Neural Information Processing Systems 18, 2005


Convex Neural Networks
Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau and Patrice Marcotte
Advances in Neural Information Processing Systems 18, 2005


Augmented Rescorla-Wagner and Maximum Likelihood Estimation
Alan L. Yuille
Advances in Neural Information Processing Systems 18, 2005


Dual-Tree Fast Gauss Transforms
Dongryeol Lee, Andrew W. Moore and Alexander G. Gray
Advances in Neural Information Processing Systems 18, 2005


Kernelized Infomax Clustering
David Barber and Felix V. Agakov
Advances in Neural Information Processing Systems 18, 2005


Ideal Observers for Detecting Motion: Correspondence Noise
Hongjing Lu and Alan L. Yuille
Advances in Neural Information Processing Systems 18, 2005


Size Regularized Cut for Data Clustering
Yixin Chen, Ya Zhang and Xiang Ji
Advances in Neural Information Processing Systems 18, 2005


Integrate-and-Fire models with adaptation are good enough
Renaud Jolivet, Alexander Rauch, Hans-rudolf Lüscher and Wulfram Gerstner
Advances in Neural Information Processing Systems 18, 2005


Data-Driven Online to Batch Conversions
Ofer Dekel and Yoram Singer
Advances in Neural Information Processing Systems 18, 2005


Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification
Ashish Kapoor, Hyungil Ahn, Yuan Qi and Rosalind W. Picard
Advances in Neural Information Processing Systems 18, 2005


Gaussian Process Dynamical Models
Jack Wang, Aaron Hertzmann and David M. Blei
Advances in Neural Information Processing Systems 18, 2005


Efficient Estimation of OOMs
Herbert Jaeger, Mingjie Zhao and Andreas Kolling
Advances in Neural Information Processing Systems 18, 2005


A Hierarchical Compositional System for Rapid Object Detection
Long Zhu and Alan L. Yuille
Advances in Neural Information Processing Systems 18, 2005


Sparse Gaussian Processes using Pseudo-inputs
Edward Snelson and Zoubin Ghahramani
Advances in Neural Information Processing Systems 18, 2005


Non-Local Manifold Parzen Windows
Yoshua Bengio, Hugo Larochelle and Pascal Vincent
Advances in Neural Information Processing Systems 18, 2005


Noise and the two-thirds power Law
Uri Maoz, Elon Portugaly, Tamar Flash and Yair Weiss
Advances in Neural Information Processing Systems 18, 2005


Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction
Guido Nolte, Andreas Ziehe, Frank Meinecke and Klaus-robert Müller
Advances in Neural Information Processing Systems 18, 2005


Fixing two weaknesses of the Spectral Method
Kevin Lang
Advances in Neural Information Processing Systems 18, 2005


Estimating the wrong Markov random field: Benefits in the computation-limited setting
Martin J. Wainwright
Advances in Neural Information Processing Systems 18, 2005


Inferring Motor Programs from Images of Handwritten Digits
Vinod Nair and Geoffrey E. Hinton
Advances in Neural Information Processing Systems 18, 2005


A Bayesian Framework for Tilt Perception and Confidence
Odelia Schwartz, Peter Dayan and Terrence J. Sejnowski
Advances in Neural Information Processing Systems 18, 2005


Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions
Sridhar Mahadevan and Mauro Maggioni
Advances in Neural Information Processing Systems 18, 2005


Kernels for gene regulatory regions
Jean-philippe Vert, Robert Thurman and William S. Noble
Advances in Neural Information Processing Systems 18, 2005


On the Convergence of Eigenspaces in Kernel Principal Component Analysis
Laurent Zwald and Gilles Blanchard
Advances in Neural Information Processing Systems 18, 2005


Coarse sample complexity bounds for active learning
Sanjoy Dasgupta
Advances in Neural Information Processing Systems 18, 2005


Benchmarking Non-Parametric Statistical Tests
Mikaela Keller, Samy Bengio and Siew Y. Wong
Advances in Neural Information Processing Systems 18, 2005


Representing Part-Whole Relationships in Recurrent Neural Networks
Viren Jain, Valentin Zhigulin and H. S. Seung
Advances in Neural Information Processing Systems 18, 2005


A Domain Decomposition Method for Fast Manifold Learning
Zhenyue Zhang and Hongyuan Zha
Advances in Neural Information Processing Systems 18, 2005


Subsequence Kernels for Relation Extraction
Raymond J. Mooney and Razvan C. Bunescu
Advances in Neural Information Processing Systems 18, 2005


A matching pursuit approach to sparse Gaussian process regression
Sathiya Keerthi and Wei Chu
Advances in Neural Information Processing Systems 18, 2005


Visual Encoding with Jittering Eyes
Michele Rucci
Advances in Neural Information Processing Systems 18, 2005


Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery
Jeremy Kubica, Joseph Masiero, Robert Jedicke, Andrew Connolly and Andrew W. Moore
Advances in Neural Information Processing Systems 18, 2005


A PAC-Bayes approach to the Set Covering Machine
François Laviolette, Mario Marchand and Mohak Shah
Advances in Neural Information Processing Systems 18, 2005


The Curse of Highly Variable Functions for Local Kernel Machines
Yoshua Bengio, Olivier Delalleau and Nicolas L. Roux
Advances in Neural Information Processing Systems 18, 2005


Top-Down Control of Visual Attention: A Rational Account
Michael Shettel, Shaun Vecera and Michael C. Mozer
Advances in Neural Information Processing Systems 18, 2005


Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface
Le Song, Evian Gordon and Elly Gysels
Advances in Neural Information Processing Systems 18, 2005


Context as Filtering
Daichi Mochihashi and Yuji Matsumoto
Advances in Neural Information Processing Systems 18, 2005


Generalization in Clustering with Unobserved Features
Eyal Krupka and Naftali Tishby
Advances in Neural Information Processing Systems 18, 2005


Large-scale biophysical parameter estimation in single neurons via constrained linear regression
Misha Ahrens, Liam Paninski and Quentin J. Huys
Advances in Neural Information Processing Systems 18, 2005


Metric Learning by Collapsing Classes
Amir Globerson and Sam T. Roweis
Advances in Neural Information Processing Systems 18, 2005


Message passing for task redistribution on sparse graphs
K. Wong, Zhuo Gao and David Tax
Advances in Neural Information Processing Systems 18, 2005


Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects
Jean-pascal Pfister and Wulfram Gerstner
Advances in Neural Information Processing Systems 18, 2005


Affine Structure From Sound
Sebastian Thrun
Advances in Neural Information Processing Systems 18, 2005


Nonparametric inference of prior probabilities from Bayes-optimal behavior
Liam Paninski
Advances in Neural Information Processing Systems 18, 2005


Learning Influence among Interacting Markov Chains
Dong Zhang, Daniel Gatica-perez, Samy Bengio and Deb Roy
Advances in Neural Information Processing Systems 18, 2005


Interpolating between types and tokens by estimating power-law generators
Sharon Goldwater, Mark Johnson and Thomas L. Griffiths
Advances in Neural Information Processing Systems 18, 2005


An aVLSI Cricket Ear Model
Andre V. Schaik, Richard Reeve, Craig Jin and Tara Hamilton
Advances in Neural Information Processing Systems 18, 2005


Statistical Convergence of Kernel CCA
Kenji Fukumizu, Arthur Gretton and Francis R. Bach
Advances in Neural Information Processing Systems 18, 2005


Learning Topology with the Generative Gaussian Graph and the EM Algorithm
Michaël Aupetit
Advances in Neural Information Processing Systems 18, 2005


Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction
Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny and Klaus-robert Müller
Advances in Neural Information Processing Systems 18, 2005


Generalization to Unseen Cases
Teemu Roos, Peter Grünwald, Petri Myllymäki and Henry Tirri
Advances in Neural Information Processing Systems 18, 2005


Active Learning for Misspecified Models
Masashi Sugiyama
Advances in Neural Information Processing Systems 18, 2005


Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization
Maxim Raginsky and Svetlana Lazebnik
Advances in Neural Information Processing Systems 18, 2005


Modeling Neuronal Interactivity using Dynamic Bayesian Networks
Lei Zhang, Dimitris Samaras, Nelly Alia-klein, Nora Volkow and Rita Goldstein
Advances in Neural Information Processing Systems 18, 2005


Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger, John Blitzer and Lawrence K. Saul
Advances in Neural Information Processing Systems 18, 2005


A Bayes Rule for Density Matrices
Manfred K. Warmuth
Advances in Neural Information Processing Systems 18, 2005


Temporal Abstraction in Temporal-difference Networks
Eddie Rafols, Anna Koop and Richard S. Sutton
Advances in Neural Information Processing Systems 18, 2005


Robust Fisher Discriminant Analysis
Seung-jean Kim, Alessandro Magnani and Stephen Boyd
Advances in Neural Information Processing Systems 18, 2005


Pattern Recognition from One Example by Chopping
Francois Fleuret and Gilles Blanchard
Advances in Neural Information Processing Systems 18, 2005


Consensus Propagation
Benjamin V. Roy and Ciamac C. Moallemi
Advances in Neural Information Processing Systems 18, 2005


Tensor Subspace Analysis
Xiaofei He, Deng Cai and Partha Niyogi
Advances in Neural Information Processing Systems 18, 2005


The Information-Form Data Association Filter
Brad Schumitsch, Sebastian Thrun, Gary Bradski and Kunle Olukotun
Advances in Neural Information Processing Systems 18, 2005


Correcting sample selection bias in maximum entropy density estimation
Miroslav Dudík, Steven J. Phillips and Robert E. Schapire
Advances in Neural Information Processing Systems 18, 2005


Modeling Memory Transfer and Saving in Cerebellar Motor Learning
Naoki Masuda and Shun-ichi Amari
Advances in Neural Information Processing Systems 18, 2005


Inference with Minimal Communication: a Decision-Theoretic Variational Approach
O. P. Kreidl and Alan S. Willsky
Advances in Neural Information Processing Systems 18, 2005


Convergence and Consistency of Regularized Boosting Algorithms with Stationary $\beta$-Mixing Observations
Sanjeev Kulkarni, Aurelie C. Lozano and Robert E. Schapire
Advances in Neural Information Processing Systems 18, 2005


Rodeo: Sparse Nonparametric Regression in High Dimensions
Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 18, 2005


Learning Shared Latent Structure for Image Synthesis and Robotic Imitation
Aaron Shon, Keith Grochow, Aaron Hertzmann and Rajesh P. Rao
Advances in Neural Information Processing Systems 18, 2005


Two view learning: SVM-2K, Theory and Practice
Jason Farquhar, David Hardoon, Hongying Meng, John S. Shawe-taylor and Sándor Szedmák
Advances in Neural Information Processing Systems 18, 2005


Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation
Dmitry Malioutov, Alan S. Willsky and Jason K. Johnson
Advances in Neural Information Processing Systems 18, 2005


Learning Multiple Related Tasks using Latent Independent Component Analysis
Jian Zhang, Zoubin Ghahramani and Yiming Yang
Advances in Neural Information Processing Systems 18, 2005


A Probabilistic Approach for Optimizing Spectral Clustering
Rong Jin, Feng Kang and Chris H. Ding
Advances in Neural Information Processing Systems 18, 2005


Generalized Nonnegative Matrix Approximations with Bregman Divergences
Suvrit Sra and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 18, 2005


Bayesian Surprise Attracts Human Attention
Laurent Itti and Pierre F. Baldi
Advances in Neural Information Processing Systems 18, 2005


The Forgetron: A Kernel-Based Perceptron on a Fixed Budget
Ofer Dekel, Shai Shalev-shwartz and Yoram Singer
Advances in Neural Information Processing Systems 18, 2005


Products of ``Edge-perts
Max Welling and Peter V. Gehler
Advances in Neural Information Processing Systems 18, 2005


Optimal cue selection strategy
Vidhya Navalpakkam and Laurent Itti
Advances in Neural Information Processing Systems 18, 2005


Separation of Music Signals by Harmonic Structure Modeling
Yun-gang Zhang and Chang-shui Zhang
Advances in Neural Information Processing Systems 18, 2005


A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D Objects
David Arathorn
Advances in Neural Information Processing Systems 18, 2005


Generalization Error Bounds for Aggregation by Mirror Descent with Averaging
Anatoli Juditsky, Alexander Nazin, Alexandre Tsybakov and Nicolas Vayatis
Advances in Neural Information Processing Systems 18, 2005


Temporally changing synaptic plasticity
Minija Tamosiunaite, Bernd Porr and Florentin Wörgötter
Advances in Neural Information Processing Systems 18, 2005


On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal?
Michael Schmitt and Laura Martignon
Advances in Neural Information Processing Systems 18, 2005


Learning Cue-Invariant Visual Responses
Jarmo Hurri
Advances in Neural Information Processing Systems 18, 2005


Assessing Approximations for Gaussian Process Classification
Malte Kuss and Carl E. Rasmussen
Advances in Neural Information Processing Systems 18, 2005


Variational Bayesian Stochastic Complexity of Mixture Models
Kazuho Watanabe and Sumio Watanabe
Advances in Neural Information Processing Systems 18, 2005


Comparing the Effects of Different Weight Distributions on Finding Sparse Representations
Bhaskar D. Rao and David P. Wipf
Advances in Neural Information Processing Systems 18, 2005


Laplacian Score for Feature Selection
Xiaofei He, Deng Cai and Partha Niyogi
Advances in Neural Information Processing Systems 18, 2005


Asymptotics of Gaussian Regularized Least Squares
Ross Lippert and Ryan Rifkin
Advances in Neural Information Processing Systems 18, 2005


Improved risk tail bounds for on-line algorithms
Nicolò Cesa-bianchi and Claudio Gentile
Advances in Neural Information Processing Systems 18, 2005


Infinite latent feature models and the Indian buffet process
Zoubin Ghahramani and Thomas L. Griffiths
Advances in Neural Information Processing Systems 18, 2005


Fast biped walking with a reflexive controller and real-time policy searching
Tao Geng, Bernd Porr and Florentin Wörgötter
Advances in Neural Information Processing Systems 18, 2005


Response Analysis of Neuronal Population with Synaptic Depression
Wentao Huang, Licheng Jiao, Shan Tan and Maoguo Gong
Advances in Neural Information Processing Systems 18, 2005


Neural mechanisms of contrast dependent receptive field size in V1
Jim Wielaard and Paul Sajda
Advances in Neural Information Processing Systems 18, 2005


TD(0) Leads to Better Policies than Approximate Value Iteration
Benjamin V. Roy
Advances in Neural Information Processing Systems 18, 2005


Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application
Joseph F. Murray, Gordon F. Hughes and Kenneth Kreutz-delgado
Journal of Machine Learning Research, 2005


A Generalization Error for Q-Learning
Susan A. Murphy
Journal of Machine Learning Research, 2005


Asymptotics in Empirical Risk Minimization
Leila Mohammadi and Sara Geer
Journal of Machine Learning Research, 2005


Learning the Kernel Function via Regularization
Charles A. Micchelli and Massimiliano Pontil
Journal of Machine Learning Research, 2005


Algorithmic Stability and Meta-Learning
Andreas Maurer
Journal of Machine Learning Research, 2005


Analysis of Variance of Cross-Validation Estimators of the Generalization Error
Marianthi Markatou, Hong Tian, Shameek Biswas and George Hripcsak
Journal of Machine Learning Research, 2005


Learning with Decision Lists of Data-Dependent Features
Mario Marchand and Marina Sokolova
Journal of Machine Learning Research, 2005


Active Learning to Recognize Multiple Types of Plankton
Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen and Thomas Hopkins
Journal of Machine Learning Research, 2005


Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
Neil D. Lawrence
Journal of Machine Learning Research, 2005


Tutorial on Practical Prediction Theory for Classification
John Langford
Journal of Machine Learning Research, 2005


Diffusion Kernels on Statistical Manifolds
John D. Lafferty and Guy Lebanon
Journal of Machine Learning Research, 2005


Assessing Approximate Inference for Binary Gaussian Process Classification
Malte Kuss and Carl E. Rasmussen
Journal of Machine Learning Research, 2005


Dimension Reduction in Text Classification with Support Vector Machines
Hyunsoo Kim, Peg Howland and Haesun Park
Journal of Machine Learning Research, 2005


Maximum Margin Algorithms with Boolean Kernels
Roni Khardon and Rocco A. Servedio
Journal of Machine Learning Research, 2005


A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
S. S. Keerthi and Dennis Decoste
Journal of Machine Learning Research, 2005


Estimating Functions for Blind Separation When Sources Have Variance Dependencies
Motoaki Kawanabe and Klaus-robert Müller
Journal of Machine Learning Research, 2005


Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes
Savina A. Jaeger
Journal of Machine Learning Research, 2005


Loopy Belief Propagation: Convergence and Effects of Message Errors
Alexander T. Ihler, John Iii and Alan S. Willsky
Journal of Machine Learning Research, 2005


Estimation of Non-Normalized Statistical Models by Score Matching
Aapo Hyvärinen
Journal of Machine Learning Research, 2005


Adaptive Online Prediction by Following the Perturbed Leader
Marcus Hutter and Jan Poland
Journal of Machine Learning Research, 2005


Convergence Theorems for Generalized Alternating Minimization Procedures
Asela Gunawardana and William Byrne
Journal of Machine Learning Research, 2005


Kernel Methods for Measuring Independence
Arthur Gretton, Ralf Herbrich, Olivier Bousquet, Bernhard Schölkopf and Alex J. Smola
Journal of Machine Learning Research, 2005


New Horn Revision Algorithms
Judy Goldsmith and Robert H. Sloan
Journal of Machine Learning Research, 2005


Quasi-Geodesic Neural Learning Algorithms Over the Orthogonal Group: A Tutorial
Simone Fiori
Journal of Machine Learning Research, 2005


Working Set Selection Using Second Order Information for Training Support Vector Machines
Rong-en Fan, Pai-hsuen Chen and Chih-jen Lin
Journal of Machine Learning Research, 2005


Learning Multiple Tasks with Kernel Methods
Theodoros Evgeniou, Charles A. Micchelli and Massimiliano Pontil
Journal of Machine Learning Research, 2005


Tree-Based Batch Mode Reinforcement Learning
Damien Ernst, Pierre Geurts and Louis Wehenkel
Journal of Machine Learning Research, 2005


Stability of Randomized Learning Algorithms
André Elisseeff, Theodoros Evgeniou and Massimiliano Pontil
Journal of Machine Learning Research, 2005


Learning Hidden Variable Networks: The Information Bottleneck Approach
Gal Elidan and Nir Friedman
Journal of Machine Learning Research, 2005


Multiclass Boosting for Weak Classifiers
Günther Eibl and Karl P. Pfeiffer
Journal of Machine Learning Research, 2005


Concentration Bounds for Unigram Language Models
Evgeny Drukh and Yishay Mansour
Journal of Machine Learning Research, 2005


On the Nystr{\"o}m Method for Approximating a Gram Matrix for Improved Kernel-Based Learning
Petros Drineas and Michael W. Mahoney
Journal of Machine Learning Research, 2005


Smooth epsiloon-Insensitive Regression by Loss Symmetrization
Ofer Dekel, Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2005


A Bayesian Model for Supervised Clustering with the Dirichlet Process Prior
Daniel Marcu and Hal Daume
Journal of Machine Learning Research, 2005


Semigroup Kernels on Measures
Marco Cuturi, Kenji Fukumizu and Jean-philippe Vert
Journal of Machine Learning Research, 2005


Local Propagation in Conditional Gaussian Bayesian Networks
Robert G. Cowell
Journal of Machine Learning Research, 2005


Gaussian Processes for Ordinal Regression
Wei Chu and Zoubin Ghahramani
Journal of Machine Learning Research, 2005


Information Bottleneck for Gaussian Variables
Gal Chechik, Amir Globerson, Naftali Tishby and Yair Weiss
Journal of Machine Learning Research, 2005


A Unifying View of Sparse Approximate Gaussian Process Regression
Joaquin Q. Candela and Carl E. Rasmussen
Journal of Machine Learning Research, 2005


Managing Diversity in Regression Ensembles
Gavin Brown, Jeremy L. Wyatt and Peter Tino
Journal of Machine Learning Research, 2005


A Bayes Optimal Approach for Partitioning the Values of Categorical Attributes
Marc Boullé
Journal of Machine Learning Research, 2005


Fast Kernel Classifiers with Online and Active Learning
Antoine Bordes, Seyda Ertekin, Jason Weston and Léon Bottou
Journal of Machine Learning Research, 2005


Active Coevolutionary Learning of Deterministic Finite Automata
Josh C. Bongard and Hod Lipson
Journal of Machine Learning Research, 2005


Universal Algorithms for Learning Theory Part I : Piecewise Constant Functions
Peter Binev, Albert Cohen, Wolfgang Dahmen, Ronald A. Devore and Vladimir N. Temlyakov
Journal of Machine Learning Research, 2005


Learning a Mahalanobis Metric from Equivalence Constraints
Aharon Bar-hillel, Tomer Hertz, Noam Shental and Daphna Weinshall
Journal of Machine Learning Research, 2005


Clustering with Bregman Divergences
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon and Joydeep Ghosh
Journal of Machine Learning Research, 2005


Clustering on the Unit Hypersphere using von Mises-Fisher Distributions
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh and Suvrit Sra
Journal of Machine Learning Research, 2005


A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
Rie K. Ando and Tong Zhang
Journal of Machine Learning Research, 2005


Separating a Real-Life Nonlinear Image Mixture
Luis B. Almeida
Journal of Machine Learning Research, 2005


Multiclass Classification with Multi-Prototype Support Vector Machines
Fabio Aiolli and Alessandro Sperduti
Journal of Machine Learning Research, 2005


Generalization Bounds for the Area Under the ROC Curve
Shivani Agarwal, Thore Graepel, Ralf Herbrich, Sariel Har-peled and Dan Roth
Journal of Machine Learning Research, 2005