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All publications at Proceedings of the 22nd International Conference on Machine Learning (ICML-05)
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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