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All publications at Proceedings of the 21st International Conference on Machine Learning (ICML-04)
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Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
Zhihua Zhang, Dit-yan Yeung and James T. Kwok
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Probabilistic score estimation with piecewise logistic regression
Jian Zhang and Yiming Yang
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Zhihua Zhang, James T. Kwok and Dit-yan Yeung
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Solving large scale linear prediction problems using stochastic gradient descent algorithms
Tong Zhang
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning and evaluating classifiers under sample selection bias
Bianca Zadrozny
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Feature extraction via generalized uncorrelated linear discriminant analysis
Jieping Ye, Ravi Janardan, Qi Li and Haesun Park
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Generalized low rank approximations of matrices
Jieping Ye
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Bayesian haplo-type inference via the dirichlet process
Eric P. Xing, Roded Sharan and Michael I. Jordan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Improving SVM accuracy by training on auxiliary data sources
Pengcheng Wu and Thomas G. Dietterich
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


P3VI: a partitioned, prioritized, parallel value iterator
David Wingate and Kevin D. Seppi
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Utile distinction hidden Markov models
Daan Wierstra and Marco Wiering
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Approximate inference by Markov chains on union spaces
Max Welling, Michal Rosen-zvi and Yee W. Teh
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning a kernel matrix for nonlinear dimensionality reduction
Kilian Q. Weinberger, Fei Sha and Lawrence K. Saul
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A hierarchical method for multi-class support vector machines
Volkan Vural and Jennifer G. Dy
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Support vector machine learning for interdependent and structured output spaces
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims and Yasemin Altun
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning random walk models for inducing word dependency distributions
Kristina Toutanova, Christopher D. Manning and Andrew Y. Ng
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning associative Markov networks
Vassil Chatalbashev, Daphne Koller and Ben Taskar
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


SVM-based generalized multiple-instance learning via approximate box counting
Qingping Tao, Stephen D. Scott, N. V. Vinodchandran and Thomas T. Osugi
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Interpolation-based Q-learning
Csaba Szepesvári and William D. Smart
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
Charles A. Sutton, Khashayar Rohanimanesh and Andrew Mccallum
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Automated hierarchical mixtures of probabilistic principal component analyzers
Ting Su and Jennifer G. Dy
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Efficient hierarchical MCMC for policy search
Malcolm Strens
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Generative modeling for continuous non-linearly embedded visual inference
Cristian Sminchisescu and Allan D. Jepson
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Using relative novelty to identify useful temporal abstractions in reinforcement learning
Özgür Simsek and Andrew G. Barto
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Online and batch learning of pseudo-metrics
Shai Shalev-shwartz, Yoram Singer and Andrew Y. Ng
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Coalition calculation in a dynamic agent environment
Ted Scully, Michael G. Madden and Gerard Lyons
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Online learning of conditionally I.I.D. data
Daniil Ryabko
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning
Matthew R. Rudary, Satinder P. Singh and Martha E. Pollack
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Towards tight bounds for rule learning
Ulrich Rückert and Stefan Kramer
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Model selection via the AUC
Saharon Rosset
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning low dimensional predictive representations
Matthew Rosencrantz, Geoffrey J. Gordon and Sebastian Thrun
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning to cluster using local neighborhood structure
Rómer Rosales, Kannan Achan and Brendan J. Frey
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Sequential skewing: an improved skewing algorithm
Soumya Ray and David Page
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Predictive automatic relevance determination by expectation propagation
Yuan (. Qi, Thomas P. Minka, Rosalind W. Picard and Zoubin Ghahramani
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Incremental learning of linear model trees
Duncan Potts
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Apprenticeship learning via inverse reinforcement learning
Pieter Abbeel and Andrew Y. Ng
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A maximum entropy approach to species distribution modeling
Steven J. Phillips, Miroslav Dudík and Robert E. Schapire
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Distribution kernels based on moments of counts
Corinna Cortes and Mehryar Mohri
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning with non-positive kernels
Cheng S. Ong, Xavier Mary, Stéphane Canu and Alex J. Smola
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Decentralized detection and classification using kernel methods
Xuanlong Nguyen, Martin J. Wainwright and Michael I. Jordan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Active learning using pre-clustering
Hieu T. Nguyen and Arnold Smeulders
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numao and Takashi Okada
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning to fly by combining reinforcement learning with behavioural cloning
Eduardo F. Morales and Claude Sammut
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Convergence of synchronous reinforcement learning with linear function approximation
Artur Merke and Ralf Schoknecht
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Diverse ensembles for active learning
Prem Melville and Raymond J. Mooney
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


The multiple multiplicative factor model for collaborative filtering
Benjamin M. Marlin and Richard S. Zemel
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Bias and variance in value function estimation
Shie Mannor, Duncan Simester, Peng Sun and John N. Tsitsiklis
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Dynamic abstraction in reinforcement learning via clustering
Shie Mannor, Ishai Menache, Amit Hoze and Uri Klein
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Extensions of marginalized graph kernels
Pierre Mahé, Nobuhisa Ueda, Tatsuya Akutsu, Jean-luc Perret and Jean-philippe Vert
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Decision trees with minimal costs
Charles X. Ling, Qiang Yang, Jianning Wang and Shichao Zhang
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Entropy-based criterion in categorical clustering
Tao Li, Sheng Ma and Mitsunori Ogihara
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Probabilistic tangent subspace: a unified view
Jianguo Lee, Jingdong Wang, Changshui Zhang and Zhaoqi Bian
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Hyperplane margin classifiers on the multinomial manifold
Guy Lebanon and John D. Lafferty
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning to learn with the informative vector machine
Neil D. Lawrence and John C. Platt
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Kernel conditional random fields: representation and clique selection
John D. Lafferty, Xiaojin Zhu and Yan Liu
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Leveraging the margin more carefully
Nir Krause and Yoram Singer
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Authorship verification as a one-class classification problem
Moshe Koppel and Jonathan Schler
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Sparse cooperative Q-learning
Jelle R. Kok and Nikos A. Vlassis
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Gradient LASSO for feature selection
Yongdai Kim and Jinseog Kim
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Bellman goes relational
Kristian Kersting, Martijn V. Otterlo and Luc D. Raedt
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
Hisashi Kashima and Yuta Tsuboi
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Robust feature induction for support vector machines
Rong Jin and Huan Liu
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A spatio-temporal extension to Isomap nonlinear dimension reduction
Odest C. Jenkins and Maja J. Mataric
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Multi-task feature and kernel selection for SVMs
Tony Jebara
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Boosting grammatical inference with confidence oracles
Jean-christophe Janodet, Richard Nock, Marc Sebban and Henri-maxime Suchier
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning and discovery of predictive state representations in dynamical systems with reset
Michael R. James and Satinder P. Singh
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Testing the significance of attribute interactions
Aleks Jakulin and Ivan Bratko
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning large margin classifiers locally and globally
Kaizhu Huang, Haiqin Yang, Irwin King and Michael R. Lyu
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Boosting margin based distance functions for clustering
Tomer Hertz, Aharon Bar-hillel and Daphna Weinshall
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Optimising area under the ROC curve using gradient descent
Alan Herschtal and Bhavani Raskutti
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A theoretical characterization of linear SVM-based feature selection
Douglas P. Hardin, Ioannis Tsamardinos and Constantin F. Aliferis
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A kernel view of the dimensionality reduction of manifolds
Jihun Ham, Daniel D. Lee, Sebastian Mika and Bernhard Schölkopf
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning Bayesian network classifiers by maximizing conditional likelihood
Daniel Grossman and Pedro Domingos
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Parameter space exploration with Gaussian process trees
Robert B. Gramacy, Herbert Lee and William G. Macready
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Tractable learning of large Bayes net structures from sparse data
Anna Goldenberg and Andrew Moore
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Margin based feature selection - theory and algorithms
Ran Gilad-bachrach, Amir Navot and Naftali Tishby
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A MFoM learning approach to robust multiclass multi-label text categorization
Sheng Gao, Wen Wu, Chin-hui Lee and Tat-seng Chua
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Evgeniy Gabrilovich and Shaul Markovitch
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A fast iterative algorithm for fisher discriminant using heterogeneous kernels
Glenn Fung, Murat Dundar, Jinbo Bi and R. B. Rao
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Ensembles of nested dichotomies for multi-class problems
Eibe Frank and Stefan Kramer
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A pitfall and solution in multi-class feature selection for text classification
George Forman
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Delegating classifiers
César Ferri, Peter A. Flach and José Hernández-orallo
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Relational sequential inference with reliable observations
Alan Fern and Robert Givan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Solving cluster ensemble problems by bipartite graph partitioning
Xiaoli Z. Fern, Russ Greiner and Dale Schuurmans
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A Monte Carlo analysis of ensemble classification
Roberto Esposito and Lorenza Saitta
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Lookahead-based algorithms for anytime induction of decision trees
Saher Esmeir and Shaul Markovitch
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning probabilistic motion models for mobile robots
Austin I. Eliazar and Ronald Parr
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


{\it K}-means clustering via principal component analysis
Chris Ding and Xiaofeng He
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Linearized cluster assignment via spectral ordering
Chris Ding and Xiaofeng He
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Training conditional random fields via gradient tree boosting
Thomas G. Dietterich, Adam Ashenfelter and Yaroslav Bulatov
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Large margin hierarchical classification
Ofer Dekel, Joseph Keshet and Yoram Singer
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


The Bayesian backfitting relevance vector machine
Aaron D'souza, Sethu Vijayakumar and Stefan Schaal
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A needle in a haystack: local one-class optimization
Koby Crammer and Gal Chechik
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Distribution kernels based on moments of counts
Corinna Cortes and Mehryar Mohri
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Communication complexity as a lower bound for learning in games
Vincent Conitzer and Tuomas Sandholm
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Links between perceptrons, MLPs and SVMs
Ronan Collobert and Samy Bengio
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Take a walk and cluster genes: a TSP-based approach to optimal rearrangement clustering
Sharlee Climer and Weixiong Zhang
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A graphical model for protein secondary structure prediction
Wei Chu, Zoubin Ghahramani and David L. Wild
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Locally linear metric adaptation for semi-supervised clustering
Hong Chang and Dit-yan Yeung
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning
Lourdes P. Castillo and Stefan Wrobel
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Ensemble selection from libraries of models
Rich Caruana, Alexandru Niculescu-mizil, Geoff Crew and Alex Ksikes
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Active learning of label ranking functions
Klaus Brinker
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Co-EM support vector learning
Ulf Brefeld and Tobias Scheffer
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Estimating replicability of classifier learning experiments
Remco R. Bouckaert
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Nonparametric classification with polynomial MPMC cascades
Sander M. Bohte, Markus Breitenbach and Gregory Z. Grudic
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Semi-supervised learning using randomized mincuts
Avrim Blum, John D. Lafferty, Mugizi R. Rwebangira and Rajashekar Reddy
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Variational methods for the Dirichlet process
David M. Blei and Michael I. Jordan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Integrating constraints and metric learning in semi-supervised clustering
Mikhail Bilenko, Sugato Basu and Raymond J. Mooney
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


C4.5 competence map: a phase transition-inspired approach
Nicolas Baskiotis and Mich\`ele Sebag
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Unifying collaborative and content-based filtering
Justin Basilico and Thomas Hofmann
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


An information theoretic analysis of maximum likelihood mixture estimation for exponential families
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh and Srujana Merugu
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Feature subset selection for learning preferences: a case study
Antonio Bahamonde, Gustavo F. Bayón, Jorge D\'ıez, José R. Quevedo, Oscar Luaces, Juan Coz, Jaime Alonso and Félix Goyache
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Multiple kernel learning, conic duality, and the SMO algorithm
Francis R. Bach, Gert Lanckriet and Michael I. Jordan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Redundant feature elimination for multi-class problems
Annalisa Appice, Michelangelo Ceci, Simon Rawles and Peter A. Flach
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Gaussian process classification for segmenting and annotating sequences
Yasemin Altun, Thomas Hofmann and Alex J. Smola
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A multiplicative up-propagation algorithm
Jong-hoon Ahn, Seungjin Choi and Jong-hoon Oh
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Learning to track 3D human motion from silhouettes
Ankur Agarwal and Bill Triggs
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004