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Maximum Entropy Discrimination Markov Networks
Jun Zhu and Eric P. Xing
Journal of Machine Learning Research, 2009


Reproducing Kernel Banach Spaces for Machine Learning
Haizhang Zhang, Yuesheng Xu and Jun Zhang
Journal of Machine Learning Research, 2009


On the Consistency of Feature Selection using Greedy Least Squares Regression
Tong Zhang
Journal of Machine Learning Research, 2009


Consistency and Localizability
Alon Zakai and Yaacov Ritov
Journal of Machine Learning Research, 2009


Bayesian Network Structure Learning by Recursive Autonomy Identification
Raanan Yehezkel and Boaz Lerner
Journal of Machine Learning Research, 2009


Learning Linear Ranking Functions for Beam Search with Application to Planning
Yuehua Xu, Alan Fern and Sung W. Yoon
Journal of Machine Learning Research, 2009


Robustness and Regularization of Support Vector Machines
Huan Xu, Constantine Caramanis and Shie Mannor
Journal of Machine Learning Research, 2009


Refinement of Reproducing Kernels
Yuesheng Xu and Haizhang Zhang
Journal of Machine Learning Research, 2009


Classification with Gaussians and Convex Loss
Dao-hong Xiang and Ding-xuan Zhou
Journal of Machine Learning Research, 2009


Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training
Kristian Woodsend and Jacek Gondzio
Journal of Machine Learning Research, 2009


Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning
Halbert White and Karim Chalak
Journal of Machine Learning Research, 2009


Distance Metric Learning for Large Margin Nearest Neighbor Classification
Kilian Q. Weinberger and Lawrence K. Saul
Journal of Machine Learning Research, 2009


On Efficient Large Margin Semisupervised Learning: Method and Theory
Junhui Wang, Xiaotong Shen and Wei Pan
Journal of Machine Learning Research, 2009


Using Local Dependencies within Batches to Improve Large Margin Classifiers
Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy and R. B. Rao
Journal of Machine Learning Research, 2009


Prediction With Expert Advice For The Brier Game
Vladimir Vovk and Fedor Zhdanov
Journal of Machine Learning Research, 2009


Properties of Monotonic Effects on Directed Acyclic Graphs
Tyler J. Vanderweele and James M. Robins
Journal of Machine Learning Research, 2009


Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
Eugene Tuv, Alexander Borisov, George C. Runger and Kari Torkkola
Journal of Machine Learning Research, 2009


Transfer Learning for Reinforcement Learning Domains: A Survey
Matthew E. Taylor and Peter Stone
Journal of Machine Learning Research, 2009


RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments
Brian Tanner and Adam M. White
Journal of Machine Learning Research, 2009


Learning Approximate Sequential Patterns for Classification
Zeeshan Syed, Piotr Indyk and John V. Guttag
Journal of Machine Learning Research, 2009


Subgroup Analysis via Recursive Partitioning
Xiaogang Su, Chih-ling Tsai, Hansheng Wang, David M. Nickerson and Bogong Li
Journal of Machine Learning Research, 2009


Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks
Nikolai Slobodianik, Dmitry Zaporozhets and Neal Madras
Journal of Machine Learning Research, 2009


The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models
Ricardo Silva and Zoubin Ghahramani
Journal of Machine Learning Research, 2009


Hash Kernels for Structured Data
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, S. Vishwanathan and Alex J. Smola
Journal of Machine Learning Research, 2009


Nonlinear Models Using Dirichlet Process Mixtures
Babak Shahbaba and Radford M. Neal
Journal of Machine Learning Research, 2009


Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data
Abhik Shah and Peter J. Woolf
Journal of Machine Learning Research, 2009


The P-Norm Push: A Simple Convex Ranking Algorithm that Concentrates at the Top of the List
Cynthia Rudin
Journal of Machine Learning Research, 2009


Margin-based Ranking and an Equivalence between AdaBoost and RankBoost
Cynthia Rudin and Robert E. Schapire
Journal of Machine Learning Research, 2009


Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression
Saharon Rosset
Journal of Machine Learning Research, 2009


Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods
Christian Rieger and Barbara Zwicknagl
Journal of Machine Learning Research, 2009


Polynomial-Delay Enumeration of Monotonic Graph Classes
Jan Ramon and Siegfried Nijssen
Journal of Machine Learning Research, 2009


Model Monitor ({\it M}$^{\mbox{2}}$): Evaluating, Comparing, and Monitoring Models
Troy Raeder and Nitesh V. Chawla
Journal of Machine Learning Research, 2009


Estimating Labels from Label Proportions
Novi Quadrianto, Alex J. Smola, Tibério S. Caetano and Quoc V. Le
Journal of Machine Learning Research, 2009


An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity
José M. Peña, Roland Nilsson, Johan Björkegren and Jesper Tegnér
Journal of Machine Learning Research, 2009


Perturbation Corrections in Approximate Inference: Mixture Modelling Applications
Ulrich Paquet, Ole Winther and Manfred Opper
Journal of Machine Learning Research, 2009


Bounded Kernel-Based Online Learning
Francesco Orabona, Joseph Keshet and Barbara Caputo
Journal of Machine Learning Research, 2009


Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining
Petra K. Novak, Nada Lavrac and Geoffrey I. Webb
Journal of Machine Learning Research, 2009


Distributed Algorithms for Topic Models
David Newman, Arthur U. Asuncion, Padhraic Smyth and Max Welling
Journal of Machine Learning Research, 2009


Cautious Collective Classification
Luke Mcdowell, Kalyan M. Gupta and David W. Aha
Journal of Machine Learning Research, 2009


Nonextensive Information Theoretic Kernels on Measures
André Martins, Noah A. Smith, Eric P. Xing, Pedro Aguiar and Mário Figueiredo
Journal of Machine Learning Research, 2009


Online Learning with Sample Path Constraints
Shie Mannor, John N. Tsitsiklis and Jia Y. Yu
Journal of Machine Learning Research, 2009


Learning When Concepts Abound
Omid Madani, Michael Connor and Wiley Greiner
Journal of Machine Learning Research, 2009


The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
Han Liu, John D. Lafferty and Larry A. Wasserman
Journal of Machine Learning Research, 2009


Marginal Likelihood Integrals for Mixtures of Independence Models
Shaowei Lin, Bernd Sturmfels and Zhiqiang Xu
Journal of Machine Learning Research, 2009


Multi-task Reinforcement Learning in Partially Observable Stochastic Environments
Hui Li, Xuejun Liao and Lawrence Carin
Journal of Machine Learning Research, 2009


Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm
Junning Li and Z. J. Wang
Journal of Machine Learning Research, 2009


DL-Learner: Learning Concepts in Description Logics
Jens Lehmann
Journal of Machine Learning Research, 2009


Exploring Strategies for Training Deep Neural Networks
Hugo Larochelle, Yoshua Bengio, Jérôme Louradour and Pascal Lamblin
Journal of Machine Learning Research, 2009


Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li and Tong Zhang
Journal of Machine Learning Research, 2009


An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs
M. P. Kumar, Vladimir Kolmogorov and Philip Torr
Journal of Machine Learning Research, 2009


Low-Rank Kernel Learning with Bregman Matrix Divergences
Brian Kulis, Mátyás A. Sustik and Inderjit S. Dhillon
Journal of Machine Learning Research, 2009


Universal Kernel-Based Learning with Applications to Regular Languages
Leonid Kontorovich and Boaz Nadler
Journal of Machine Learning Research, 2009


Learning Halfspaces with Malicious Noise
Adam R. Klivans, Philip M. Long and Rocco A. Servedio
Journal of Machine Learning Research, 2009


Dlib-ml: A Machine Learning Toolkit
Davis E. King
Journal of Machine Learning Research, 2009


Markov Properties for Linear Causal Models with Correlated Errors
Changsung Kang and Jin Tian
Journal of Machine Learning Research, 2009


A Least-squares Approach to Direct Importance Estimation
Takafumi Kanamori, Shohei Hido and Masashi Sugiyama
Journal of Machine Learning Research, 2009


On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality
Wenxin Jiang
Journal of Machine Learning Research, 2009


Structure Spaces
Brijnesh J. Jain and Klaus Obermayer
Journal of Machine Learning Research, 2009


Fourier Theoretic Probabilistic Inference over Permutations
Jonathan Huang, Carlos Guestrin and Leonidas J. Guibas
Journal of Machine Learning Research, 2009


Online Learning with Samples Drawn from Non-identical Distributions
Ting Hu and Ding-xuan Zhou
Journal of Machine Learning Research, 2009


Learning Permutations with Exponential Weights
David P. Helmbold and Manfred K. Warmuth
Journal of Machine Learning Research, 2009


Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions
Lisa Hellerstein, Bernard Rosell, Eric Bach, Soumya Ray and David Page
Journal of Machine Learning Research, 2009


Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks
Jean Hausser and Korbinian Strimmer
Journal of Machine Learning Research, 2009


A Survey of Accuracy Evaluation Metrics of Recommendation Tasks
Asela Gunawardana and Guy Shani
Journal of Machine Learning Research, 2009


Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification
Eitan Greenshtein and Junyong Park
Journal of Machine Learning Research, 2009


Evolutionary Model Type Selection for Global Surrogate Modeling
Dirk Gorissen, Tom Dhaene and Filip D. Turck
Journal of Machine Learning Research, 2009


Robust Process Discovery with Artificial Negative Events
Stijn Goedertier, David Martens, Jan Vanthienen and Bart Baesens
Journal of Machine Learning Research, 2009


NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM
Pradip Ghanty, Samrat Paul and Nikhil R. Pal
Journal of Machine Learning Research, 2009


Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization
Vojtech Franc and Sören Sonnenburg
Journal of Machine Learning Research, 2009


Stable and Efficient Gaussian Process Calculations
Leslie Foster, Alex Waagen, Nabeela Aijaz, Michael Hurley, Apolonio Luis, Joel Rinsky, Chandrika Satyavolu, Michael J. Way, Paul R. Gazis and Ashok Srivastava
Journal of Machine Learning Research, 2009


Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods
Holger Höfling and Robert Tibshirani
Journal of Machine Learning Research, 2009


An Anticorrelation Kernel for Subsystem Training in Multiple Classifier Systems
Luciana Ferrer, M. K. Sönmez and Elizabeth Shriberg
Journal of Machine Learning Research, 2009


On The Power of Membership Queries in Agnostic Learning
Vitaly Feldman
Journal of Machine Learning Research, 2009


Ultrahigh Dimensional Feature Selection: Beyond The Linear Model
Jianqing Fan, Richard Samworth and Yichao Wu
Journal of Machine Learning Research, 2009


CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning
Roberto Esposito and Daniele P. Radicioni
Journal of Machine Learning Research, 2009


Particle Swarm Model Selection
Hugo J. Escalante, Manuel Montes-y-gómez and Luis E. Sucar
Journal of Machine Learning Research, 2009


Incorporating Functional Knowledge in Neural Networks
Charles Dugas, Yoshua Bengio, Françcois Bélisle, Claude Nadeau and René Garcia
Journal of Machine Learning Research, 2009


Efficient Online and Batch Learning Using Forward Backward Splitting
John C. Duchi and Yoram Singer
Journal of Machine Learning Research, 2009


Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors
Mathias Drton, Michael Eichler and Thomas S. Richardson
Journal of Machine Learning Research, 2009


Analysis of Perceptron-Based Active Learning
Sanjoy Dasgupta, Adam T. Kalai and Claire Monteleoni
Journal of Machine Learning Research, 2009


Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques
Barnabás Póczos and András Lörincz
Journal of Machine Learning Research, 2009


Scalable Collaborative Filtering Approaches for Large Recommender Systems
Gábor Takács, István Pilászy, Bottyán Németh and Domonkos Tikk
Journal of Machine Learning Research, 2009


Learning Nondeterministic Classifiers
Juan Coz, Jorge D\'ıez and Antonio Bahamonde
Journal of Machine Learning Research, 2009


Fast Approximate {\it k}NN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection
Jie Chen, Haw-ren Fang and Yousef Saad
Journal of Machine Learning Research, 2009


Similarity-based Classification: Concepts and Algorithms
Yihua Chen, Eric K. Garcia, Maya R. Gupta, Ali Rahimi and Luca Cazzanti
Journal of Machine Learning Research, 2009


Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions
Sébastien Bubeck and Ulrike V. Luxburg
Journal of Machine Learning Research, 2009


Provably Efficient Learning with Typed Parametric Models
Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman and Nicholas Roy
Journal of Machine Learning Research, 2009


Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation
Facundo Bromberg and Dimitris Margaritis
Journal of Machine Learning Research, 2009


SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent
Antoine Bordes, Léon Bottou and Patrick Gallinari
Journal of Machine Learning Research, 2009


Adaptive False Discovery Rate Control under Independence and Dependence
Gilles Blanchard and Étienne Roquain
Journal of Machine Learning Research, 2009


Discriminative Learning Under Covariate Shift
Steffen Bickel, Michael Brückner and Tobias Scheffer
Journal of Machine Learning Research, 2009


Data-driven Calibration of Penalties for Least-Squares Regression
Sylvain Arlot and Pascal Massart
Journal of Machine Learning Research, 2009


When Is There a Representer Theorem? Vector Versus Matrix Regularizers
Andreas Argyriou, Charles A. Micchelli and Massimiliano Pontil
Journal of Machine Learning Research, 2009


Learning Acyclic Probabilistic Circuits Using Test Paths
Dana Angluin, James Aspnes, Jiang Chen, David Eisenstat and Lev Reyzin
Journal of Machine Learning Research, 2009


Reinforcement Learning in Finite MDPs: PAC Analysis
Alexander L. Strehl, Lihong Li and Michael L. Littman
Journal of Machine Learning Research, 2009


Generalization Bounds for Ranking Algorithms via Algorithmic Stability
Shivani Agarwal and Partha Niyogi
Journal of Machine Learning Research, 2009


A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
Jacob Abernethy, Theodoros Evgeniou, Jean-philippe Vert and Francis R. Bach
Journal of Machine Learning Research, 2009


Java-ML: A Machine Learning Library
Thomas Abeel, Yves Peer and Yvan Saeys
Journal of Machine Learning Research, 2009


Nieme: Large-Scale Energy-Based Models
Francis Maes
Journal of Machine Learning Research, 2009


A Parameter-Free Classification Method for Large Scale Learning
Marc Boullé
Journal of Machine Learning Research, 2009


Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Jun Zhu, Zaiqing Nie, Bo Zhang and Ji-rong Wen
Journal of Machine Learning Research, 2008


Causal Reasoning with Ancestral Graphs
Jiji Zhang
Journal of Machine Learning Research, 2008


Learning Control Knowledge for Forward Search Planning
Sung W. Yoon, Alan Fern and Robert Givan
Journal of Machine Learning Research, 2008


Multi-class Discriminant Kernel Learning via Convex Programming
Jieping Ye, Shuiwang Ji and Jianhui Chen
Journal of Machine Learning Research, 2008


Comments on the Complete Characterization of a Family of Solutions to a Generalized {\it Fisher} Criterion
Jieping Ye
Journal of Machine Learning Research, 2008


A Recursive Method for Structural Learning of Directed Acyclic Graphs
Xianchao Xie and Zhi Geng
Journal of Machine Learning Research, 2008


Regularization on Graphs with Function-adapted Diffusion Processes
Arthur D. Szlam, Mauro Maggioni and Ronald R. Coifman
Journal of Machine Learning Research, 2008


Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming
Ashwin Srinivasan and Ross D. King
Journal of Machine Learning Research, 2008


Complete Identification Methods for the Causal Hierarchy
Ilya Shpitser and Judea Pearl
Journal of Machine Learning Research, 2008


A Tutorial on Conformal Prediction
Glenn Shafer and Vladimir Vovk
Journal of Machine Learning Research, 2008


Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
Matthias W. Seeger
Journal of Machine Learning Research, 2008


Bayesian Inference and Optimal Design for the Sparse Linear Model
Matthias W. Seeger
Journal of Machine Learning Research, 2008


Ranking Categorical Features Using Generalization Properties
Sivan Sabato and Shai Shalev-shwartz
Journal of Machine Learning Research, 2008


Linear-Time Computation of Similarity Measures for Sequential Data
Konrad Rieck and Pavel Laskov
Journal of Machine Learning Research, 2008


Using Markov Blankets for Causal Structure Learning
Jean-philippe Pellet and André Elisseeff
Journal of Machine Learning Research, 2008


Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
Liviu Panait, Karl Tuyls and Sean Luke
Journal of Machine Learning Research, 2008


Finite-Time Bounds for Fitted Value Iteration
Rémi Munos and Csaba Szepesvári
Journal of Machine Learning Research, 2008


Evidence Contrary to the Statistical View of Boosting
David Mease and Abraham J. Wyner
Journal of Machine Learning Research, 2008


Learning Similarity with Operator-valued Large-margin Classifiers
Andreas Maurer
Journal of Machine Learning Research, 2008


Hit Miss Networks with Applications to Instance Selection
Elena Marchiori
Journal of Machine Learning Research, 2008


Maximal Causes for Non-linear Component Extraction
Jörg Lücke and Maneesh Sahani
Journal of Machine Learning Research, 2008


Aggregation of SVM Classifiers Using Sobolev Spaces
Sébastien Loustau
Journal of Machine Learning Research, 2008


Trust Region Newton Method for Logistic Regression
Chih-jen Lin, Ruby C. Weng and S. S. Keerthi
Journal of Machine Learning Research, 2008


Support Vector Machinery for Infinite Ensemble Learning
Hsuan-tien Lin and Ling Li
Journal of Machine Learning Research, 2008


Generalization from Observed to Unobserved Features by Clustering
Eyal Krupka and Naftali Tishby
Journal of Machine Learning Research, 2008


Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
Andreas Krause, Ajit P. Singh and Carlos Guestrin
Journal of Machine Learning Research, 2008


A Bahadur Representation of the Linear Support Vector Machine
Ja-yong Koo, Yoonkyung Lee, Yuwon Kim and Changyi Park
Journal of Machine Learning Research, 2008


A Library for Locally Weighted Projection Regression
Stefan Klanke, Sethu Vijayakumar and Stefan Schaal
Journal of Machine Learning Research, 2008


A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters
Zach Jorgensen, Yan Zhou and W. M. Inge
Journal of Machine Learning Research, 2008


Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
Bo Jiang, Xuegong Zhang and Tianxi Cai
Journal of Machine Learning Research, 2008


Shark
Christian Igel, Verena Heidrich-meisner and Tobias Glasmachers
Journal of Machine Learning Research, 2008


Active Learning by Spherical Subdivision
Falk-florian Henrich and Klaus Obermayer
Journal of Machine Learning Research, 2008


Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Faustino J. Gomez, Jürgen Schmidhuber and Risto Miikkulainen
Journal of Machine Learning Research, 2008


Manifold Learning: The Price of Normalization
Yair Goldberg, Alon Zakai, Dan Kushnir and Yaacov Ritov
Journal of Machine Learning Research, 2008


Closed Sets for Labeled Data
Gemma C. Garriga, Petra Kralj and Nada Lavrac
Journal of Machine Learning Research, 2008


Discriminative Learning of Max-Sum Classifiers
Vojtech Franc and Bogdan Savchynskyy
Journal of Machine Learning Research, 2008


LIBLINEAR: A Library for Large Linear Classification
Rong-en Fan, Kai-wei Chang, Cho-jui Hsieh, Xiang-rui Wang and Chih-jen Lin
Journal of Machine Learning Research, 2008


Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models
Mathias Drton and Thomas S. Richardson
Journal of Machine Learning Research, 2008


Optimal Solutions for Sparse Principal Component Analysis
Alexandre D'aspremont, Laurent E. Ghaoui and Francis R. Bach
Journal of Machine Learning Research, 2008


A New Algorithm for Estimating the Effective Dimension-Reduction Subspace
Arnak S. Dalalyan, Anatoli Juditsky and Vladimir Spokoiny
Journal of Machine Learning Research, 2008


Value Function Based Reinforcement Learning in Changing Markovian Environments
Balázs C. Csáji and László Monostori
Journal of Machine Learning Research, 2008


Learning from Multiple Sources
Koby Crammer, Michael Kearns and Jennifer Wortman
Journal of Machine Learning Research, 2008


Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
Giorgio Corani and Marco Zaffalon
Journal of Machine Learning Research, 2008


Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Michael Collins, Amir Globerson, Terry Koo, Xavier Carreras and Peter L. Bartlett
Journal of Machine Learning Research, 2008


An Information Criterion for Variable Selection in Support Vector Machines
Gerda Claeskens, Christophe Croux and Johan V. Kerckhoven
Journal of Machine Learning Research, 2008


Search for Additive Nonlinear Time Series Causal Models
Tianjiao Chu and Clark Glymour
Journal of Machine Learning Research, 2008


Bouligand Derivatives and Robustness of Support Vector Machines for Regression
Andreas Christmann and Arnout V. Messem
Journal of Machine Learning Research, 2008


Learning to Combine Motor Primitives Via Greedy Additive Regression
Manu Chhabra and Robert A. Jacobs
Journal of Machine Learning Research, 2008


Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns
Shann-ching Chen, Geoffrey J. Gordon and Robert F. Murphy
Journal of Machine Learning Research, 2008


Max-margin Classification of Data with Absent Features
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel and Daphne Koller
Journal of Machine Learning Research, 2008


Optimization Techniques for Semi-Supervised Support Vector Machines
Olivier Chapelle, Vikas Sindhwani and S. S. Keerthi
Journal of Machine Learning Research, 2008


Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Kai-wei Chang, Cho-jui Hsieh and Chih-jen Lin
Journal of Machine Learning Research, 2008


Universal Multi-Task Kernels
Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil and Yiming Ying
Journal of Machine Learning Research, 2008


On the Suitable Domain for SVM Training in Image Coding
Gustavo Camps-valls, Juan Gutierrez, Gabriel Gómez-pérez and Jesus Malo
Journal of Machine Learning Research, 2008


On Relevant Dimensions in Kernel Feature Spaces
Mikio L. Braun, Joachim M. Buhmann and Klaus-robert Müller
Journal of Machine Learning Research, 2008


Consistency of Random Forests and Other Averaging Classifiers
Gérard Biau, Luc Devroye and Gábor Lugosi
Journal of Machine Learning Research, 2008


Learning Balls of Strings from Edit Corrections
Leonor Becerra-bonache, Colin Higuera, Jean-christophe Janodet and Frédéric Tantini
Journal of Machine Learning Research, 2008


Nearly Uniform Validation Improves Compression-Based Error Bounds
Eric Bax
Journal of Machine Learning Research, 2008


An Error Bound Based on a Worst Likely Assignment
Eric Bax and Augusto Callejas
Journal of Machine Learning Research, 2008


Classification with a Reject Option using a Hinge Loss
Peter L. Bartlett and Marten H. Wegkamp
Journal of Machine Learning Research, 2008


Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
Onureena Banerjee, Laurent E. Ghaoui and Alexandre D'aspremont
Journal of Machine Learning Research, 2008


Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Suhrid Balakrishnan and David Madigan
Journal of Machine Learning Research, 2008


Consistency of the Group Lasso and Multiple Kernel Learning
Francis R. Bach
Journal of Machine Learning Research, 2008


Consistency of Trace Norm Minimization
Francis R. Bach
Journal of Machine Learning Research, 2008


Online Learning of Complex Prediction Problems Using Simultaneous Projections
Yonatan Amit, Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2008


Mixed Membership Stochastic Blockmodels
Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing
Journal of Machine Learning Research, 2008


Stagewise Lasso
Peng Zhao and Bin Yu
Journal of Machine Learning Research, 2007


Learnability of Gaussians with Flexible Variances
Yiming Ying and Ding-xuan Zhou
Journal of Machine Learning Research, 2007


Multi-Task Learning for Classification with Dirichlet Process Priors
Ya Xue, Xuejun Liao, Lawrence Carin and Balaji Krishnapuram
Journal of Machine Learning Research, 2007


Refinable Kernels
Yuesheng Xu and Haizhang Zhang
Journal of Machine Learning Research, 2007


Large Margin Semi-supervised Learning
Junhui Wang and Xiaotong Shen
Journal of Machine Learning Research, 2007


Margin Trees for High-dimensional Classification
Robert Tibshirani and Trevor Hastie
Journal of Machine Learning Research, 2007


On the Consistency of Multiclass Classification Methods
Ambuj Tewari and Peter L. Bartlett
Journal of Machine Learning Research, 2007


A Unified Continuous Optimization Framework for Center-Based Clustering Methods
Marc Teboulle
Journal of Machine Learning Research, 2007


Transfer Learning via Inter-Task Mappings for Temporal Difference Learning
Matthew E. Taylor, Peter Stone and Yaxin Liu
Journal of Machine Learning Research, 2007


Distances between Data Sets Based on Summary Statistics
Nikolaj Tatti
Journal of Machine Learning Research, 2007


Undercomplete Blind Subspace Deconvolution
Zoltán Szabó, Barnabás Póczos and András Lörincz
Journal of Machine Learning Research, 2007


Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data
Charles A. Sutton, Andrew Mccallum and Khashayar Rohanimanesh
Journal of Machine Learning Research, 2007


Covariate Shift Adaptation by Importance Weighted Cross Validation
Masashi Sugiyama, Matthias Krauledat and Klaus-robert Müller
Journal of Machine Learning Research, 2007


Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
Masashi Sugiyama
Journal of Machine Learning Research, 2007


Bayesian Quadratic Discriminant Analysis
Santosh Srivastava, Maya R. Gupta and Bela A. Frigyik
Journal of Machine Learning Research, 2007


The Need for Open Source Software in Machine Learning
Sören Sonnenburg, Mikio L. Braun, Cheng S. Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann Lecun, Klaus-robert Müller, Fernando Pereira, Carl E. Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Pascal Vincent, Jason Weston, Robert C. Williamson and Alex J. Smola
Journal of Machine Learning Research, 2007


Handling Missing Values when Applying Classification Models
Maytal Saar-tsechansky and Foster J. Provost
Journal of Machine Learning Research, 2007


Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
Philippe Rigollet
Journal of Machine Learning Research, 2007


Value Regularization and Fenchel Duality
Ryan M. Rifkin and Ross A. Lippert
Journal of Machine Learning Research, 2007


Learning Equivariant Functions with Matrix Valued Kernels
Marco Reisert and Hans Burkhardt
Journal of Machine Learning Research, 2007


Building Blocks for Variational Bayesian Learning of Latent Variable Models
Tapani Raiko, Harri Valpola, Markus Harva and Juha Karhunen
Journal of Machine Learning Research, 2007


Characterizing the Function Space for Bayesian Kernel Models
Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee and Robert L. Wolpert
Journal of Machine Learning Research, 2007


Penalized Model-Based Clustering with Application to Variable Selection
Wei Pan and Xiaotong Shen
Journal of Machine Learning Research, 2007


Infinitely Imbalanced Logistic Regression
Art B. Owen
Journal of Machine Learning Research, 2007


Synergistic Face Detection and Pose Estimation with Energy-Based Models
Margarita Osadchy, Yann Lecun and Matthew L. Miller
Journal of Machine Learning Research, 2007


Learning in Environments with Unknown Dynamics: Towards more Robust Concept Learners
Marlon N\'uñez, Ra\'ul Fidalgo and Rafael Morales
Journal of Machine Learning Research, 2007


Consistent Feature Selection for Pattern Recognition in Polynomial Time
Roland Nilsson, José M. Peña, Johan Björkegren and Jesper Tegnér
Journal of Machine Learning Research, 2007


Relational Dependency Networks
Jennifer Neville and David Jensen
Journal of Machine Learning Research, 2007


Loop Corrections for Approximate Inference on Factor Graphs
Joris M. Mooij and Hilbert J. Kappen
Journal of Machine Learning Research, 2007


Multi-class Protein Classification Using Adaptive Codes
Iain Melvin, Eugene Ie, Jason Weston, William S. Noble and Christina S. Leslie
Journal of Machine Learning Research, 2007


Concave Learners for Rankboost
Ofer Melnik, Yehuda Vardi and Cun-hui Zhang
Journal of Machine Learning Research, 2007


Boosted Classification Trees and Class Probability/Quantile Estimation
David Mease, Abraham J. Wyner and Andreas Buja
Journal of Machine Learning Research, 2007


Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes
Sridhar Mahadevan and Mauro Maggioni
Journal of Machine Learning Research, 2007


Classification in Networked Data: A Toolkit and a Univariate Case Study
Sofus A. Macskassy and Foster J. Provost
Journal of Machine Learning Research, 2007


Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"
Ga\"elle Loosli and Stéphane Canu
Journal of Machine Learning Research, 2007


A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion
Marco Loog
Journal of Machine Learning Research, 2007


Local Discriminant Wavelet Packet Coordinates for Face Recognition
Chao-chun Liu, Dao-qing Dai and Hong Yan
Journal of Machine Learning Research, 2007


General Polynomial Time Decomposition Algorithms
Nikolas List and Hans-ulrich Simon
Journal of Machine Learning Research, 2007


A Nonparametric Statistical Approach to Clustering via Mode Identification
Jia Li, Surajit Ray and Bruce G. Lindsay
Journal of Machine Learning Research, 2007


Nonlinear Estimators and Tail Bounds for Dimension Reduction in {\it l}$_{\mbox{1}}$ Using Cauchy Random Projections
Ping Li, Trevor Hastie and Kenneth W. Church
Journal of Machine Learning Research, 2007


The Locally Weighted Bag of Words Framework for Document Representation
Guy Lebanon, Yi Mao and Joshua V. Dillon
Journal of Machine Learning Research, 2007


PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers
Françcois Laviolette and Mario Marchand
Journal of Machine Learning Research, 2007


Integrating Na\"{\i}ve Bayes and FOIL
Niels Landwehr, Kristian Kersting and Luc D. Raedt
Journal of Machine Learning Research, 2007


Unlabeled Compression Schemes for Maximum Classes
Dima Kuzmin and Manfred K. Warmuth
Journal of Machine Learning Research, 2007


Measuring Differentiability: Unmasking Pseudonymous Authors
Moshe Koppel, Jonathan Schler and Elisheva Bonchek-dokow
Journal of Machine Learning Research, 2007


Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
J. Z. Kolter and Marcus A. Maloof
Journal of Machine Learning Research, 2007


An Interior-Point Method for Large-Scale {\it l}$_{\mbox{1}}$-Regularized Logistic Regression
Kwangmoo Koh, Seung-jean Kim and Stephen P. Boyd
Journal of Machine Learning Research, 2007


Noise Tolerant Variants of the Perceptron Algorithm
Roni Khardon and Gabriel Wachman
Journal of Machine Learning Research, 2007


Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm
Markus Kalisch and Peter Bühlmann
Journal of Machine Learning Research, 2007


On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning
Rie Johnson and Tong Zhang
Journal of Machine Learning Research, 2007


Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data
Zakria Hussain, Françcois Laviolette, Mario Marchand, John Shawe-taylor, S. C. Brubaker and Matthew D. Mullin
Journal of Machine Learning Research, 2007


A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning
Carine Hue and Marc Boullé
Journal of Machine Learning Research, 2007


Structure and Majority Classes in Decision Tree Learning
Ray J. Hickey
Journal of Machine Learning Research, 2007


Graph Laplacians and their Convergence on Random Neighborhood Graphs
Matthias Hein, Jean-yves Audibert and Ulrike V. Luxburg
Journal of Machine Learning Research, 2007


Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification
Onur C. Hamsici and Aleix M. Mart\'ınez
Journal of Machine Learning Research, 2007


The On-Line Shortest Path Problem Under Partial Monitoring
András György, Tamás Linder, Gábor Lugosi and György Ottucsák
Journal of Machine Learning Research, 2007


Fast Iterative Kernel Principal Component Analysis
Simon Günter, Nicol N. Schraudolph and S. Vishwanathan
Journal of Machine Learning Research, 2007


VC Theory of Large Margin Multi-Category Classifiers
Yann Guermeur
Journal of Machine Learning Research, 2007


The Pyramid Match Kernel: Efficient Learning with Sets of Features
Kristen Grauman and Trevor Darrell
Journal of Machine Learning Research, 2007


Truncating the Loop Series Expansion for Belief Propagation
Vicençc Gómez, Joris M. Mooij and Hilbert J. Kappen
Journal of Machine Learning Research, 2007


Euclidean Embedding of Co-occurrence Data
Amir Globerson, Gal Chechik, Fernando Pereira and Naftali Tishby
Journal of Machine Learning Research, 2007


Hierarchical Average Reward Reinforcement Learning
Mohammad Ghavamzadeh and Sridhar Mahadevan
Journal of Machine Learning Research, 2007


Nonlinear Boosting Projections for Ensemble Construction
Nicolás Garc\'ıa-pedrajas, Cesar Garc\'ıa-osorio and Colin Fyfe
Journal of Machine Learning Research, 2007


A Stochastic Algorithm for Feature Selection in Pattern Recognition
Sébastien Gadat and Laurent Younes
Journal of Machine Learning Research, 2007


Harnessing the Expertise of 70, 000 Human Editors: Knowledge-Based Feature Generation for Text Categorization
Evgeniy Gabrilovich and Shaul Markovitch
Journal of Machine Learning Research, 2007


Statistical Consistency of Kernel Canonical Correlation Analysis
Kenji Fukumizu, Francis R. Bach and Arthur Gretton
Journal of Machine Learning Research, 2007


Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions
Vitaly Feldman
Journal of Machine Learning Research, 2007


Anytime Learning of Decision Trees
Saher Esmeir and Shaul Markovitch
Journal of Machine Learning Research, 2007


"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks
Gal Elidan, Iftach Nachman and Nir Friedman
Journal of Machine Learning Research, 2007


Separating Models of Learning from Correlated and Uncorrelated Data
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio and Andrew Wan
Journal of Machine Learning Research, 2007


Bilinear Discriminant Component Analysis
Mads Dyrholm, Christoforos Christoforou and Lucas C. Parra
Journal of Machine Learning Research, 2007


Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling
Miroslav Dudík, Steven J. Phillips and Robert E. Schapire
Journal of Machine Learning Research, 2007


On the Representer Theorem and Equivalent Degrees of Freedom of SVR
Francesco Dinuzzo, Marta Neve, Giuseppe D. Nicolao and Ugo P. Gianazza
Journal of Machine Learning Research, 2007


Online Learning of Multiple Tasks with a Shared Loss
Ofer Dekel, Philip M. Long and Yoram Singer
Journal of Machine Learning Research, 2007


A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians
Sanjoy Dasgupta and Leonard J. Schulman
Journal of Machine Learning Research, 2007


Ranking the Best Instances
Stéphan Clémençcon and Nicolas Vayatis
Journal of Machine Learning Research, 2007


Polynomial Identification in the Limit of Substitutable Context-free Languages
Alexander Clark and Rémi Eyraud
Journal of Machine Learning Research, 2007


Behavioral Shaping for Geometric Concepts
Manu Chhabra, Robert A. Jacobs and Daniel Stefankovic
Journal of Machine Learning Research, 2007


Very Fast Online Learning of Highly Non Linear Problems
Aggelos Chariatis
Journal of Machine Learning Research, 2007


{\it Gini} Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression
Shantanu Chakrabartty and Gert Cauwenberghs
Journal of Machine Learning Research, 2007


Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
Gavin C. Cawley and Nicola Talbot
Journal of Machine Learning Research, 2007


Learning to Classify Ordinal Data: The Data Replication Method
Jaime S. Cardoso and Joaquim Costa
Journal of Machine Learning Research, 2007


Compression-Based Averaging of Selective Naive Bayes Classifiers
Marc Boullé
Journal of Machine Learning Research, 2007


From External to Internal Regret
Avrim Blum and Yishay Mansour
Journal of Machine Learning Research, 2007


Dynamics and Generalization Ability of LVQ Algorithms
Michael Biehl, Anarta Ghosh and Barbara Hammer
Journal of Machine Learning Research, 2007


AdaBoost is Consistent
Peter L. Bartlett and Mikhail Traskin
Journal of Machine Learning Research, 2007


Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results
Peter L. Bartlett and Ambuj Tewari
Journal of Machine Learning Research, 2007


A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu and Dharmendra S. Modha
Journal of Machine Learning Research, 2007


Combining PAC-Bayesian and Generic Chaining Bounds
Jean-yves Audibert and Olivier Bousquet
Journal of Machine Learning Research, 2007


Learning Horn Expressions with LOGAN-H
Marta Arias, Roni Khardon and Jérôme Maloberti
Journal of Machine Learning Research, 2007


Minimax Regret Classifier for Imprecise Class Distributions
Roc\'ıo Ala\'ız-rodr\'ıguez, Alicia Guerrero-curieses and Jes\'us Cid-sueiro
Journal of Machine Learning Research, 2007


Streamwise Feature Selection
Jing Zhou, Dean P. Foster, Robert A. Stine and Lyle H. Ungar
Journal of Machine Learning Research, 2006


On Model Selection Consistency of Lasso
Peng Zhao and Bin Yu
Journal of Machine Learning Research, 2006


Ensemble Pruning Via Semi-definite Programming
Yi Zhang, Samuel Burer and W. N. Street
Journal of Machine Learning Research, 2006


Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
Luca Zanni, Thomas Serafini and Gaetano Zanghirati
Journal of Machine Learning Research, 2006


Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
Jieping Ye and Tao Xiong
Journal of Machine Learning Research, 2006


Linear Programming Relaxations and Belief Propagation - An Empirical Study
Chen Yanover, Talya Meltzer and Yair Weiss
Journal of Machine Learning Research, 2006


A Direct Method for Building Sparse Kernel Learning Algorithms
Mingrui Wu, Bernhard Schölkopf and Gökhan H. Bakir
Journal of Machine Learning Research, 2006


On Inferring Application Protocol Behaviors in Encrypted Network Traffic
Charles V. Wright, Fabian Monrose and Gerald M. Masson
Journal of Machine Learning Research, 2006


Evolutionary Function Approximation for Reinforcement Learning
Shimon Whiteson and Peter Stone
Journal of Machine Learning Research, 2006


Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation
Kazuho Watanabe and Sumio Watanabe
Journal of Machine Learning Research, 2006


Estimating the "Wrong" Graphical Model: Benefits in the Computation-Limited Setting
Martin J. Wainwright
Journal of Machine Learning Research, 2006


Step Size Adaptation in Reproducing Kernel Hilbert Space
S. Vishwanathan, Nicol N. Schraudolph and Alex J. Smola
Journal of Machine Learning Research, 2006


Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
Régis Vert and Jean-philippe Vert
Journal of Machine Learning Research, 2006


Structured Prediction, Dual Extragradient and Bregman Projections
Benjamin Taskar, Simon Lacoste-julien and Michael I. Jordan
Journal of Machine Learning Research, 2006


Nonparametric Quantile Estimation
Ichiro Takeuchi, Quoc V. Le, Tim D. Sears and Alex J. Smola
Journal of Machine Learning Research, 2006


Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
Masashi Sugiyama
Journal of Machine Learning Research, 2006


Learning Image Components for Object Recognition
Michael W. Spratling
Journal of Machine Learning Research, 2006


Large Scale Multiple Kernel Learning
Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer and Bernhard Schölkopf
Journal of Machine Learning Research, 2006


Noisy-OR Component Analysis and its Application to Link Analysis
Tomás Singliar and Milos Hauskrecht
Journal of Machine Learning Research, 2006


Learning the Structure of Linear Latent Variable Models
Ricardo Silva, Richard Scheines, Clark Glymour and Peter Spirtes
Journal of Machine Learning Research, 2006


Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya and Alex J. Smola
Journal of Machine Learning Research, 2006


A Linear Non-Gaussian Acyclic Model for Causal Discovery
Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen and Antti J. Kerminen
Journal of Machine Learning Research, 2006


Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2006


Learning Minimum Volume Sets
Clayton Scott and Robert D. Nowak
Journal of Machine Learning Research, 2006


On the Complexity of Learning Lexicographic Strategies
Michael Schmitt and Laura Martignon
Journal of Machine Learning Research, 2006


An Efficient Implementation of an Active Set Method for SVMs
Katya Scheinberg
Journal of Machine Learning Research, 2006


A Hierarchy of Support Vector Machines for Pattern Detection
Hichem Sahbi and Donald Geman
Journal of Machine Learning Research, 2006


Pattern Recognition for Conditionally Independent Data
Daniil Ryabko
Journal of Machine Learning Research, 2006


A Graphical Representation of Equivalence Classes of AMP Chain Graphs
Alberto Roverato and Milan Studen\'y
Journal of Machine Learning Research, 2006


Kernel-Based Learning of Hierarchical Multilabel Classification Models
Juho Rousu, Craig Saunders, Sándor Szedmák and John Shawe-taylor
Journal of Machine Learning Research, 2006


Learning Parts-Based Representations of Data
David A. Ross and Richard S. Zemel
Journal of Machine Learning Research, 2006


Active Learning with Feedback on Features and Instances
Hema Raghavan, Omid Madani and Rosie Jones
Journal of Machine Learning Research, 2006


Point-Based Value Iteration for Continuous POMDPs
Josep M. Porta, Nikos A. Vlassis, Matthijs Spaan and Pascal Poupart
Journal of Machine Learning Research, 2006


MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
Dana Pe'er, Amos Tanay and Aviv Regev
Journal of Machine Learning Research, 2006


Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
Andrea Passerini, Paolo Frasconi and Luc D. Raedt
Journal of Machine Learning Research, 2006


Linear State-Space Models for Blind Source Separation
Rasmus K. Olsson and Lars K. Hansen
Journal of Machine Learning Research, 2006


Bayesian Network Learning with Parameter Constraints
Radu S. Niculescu, Tom M. Mitchell and R. B. Rao
Journal of Machine Learning Research, 2006


Policy Gradient in Continuous Time
Rémi Munos
Journal of Machine Learning Research, 2006


Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
Rémi Munos
Journal of Machine Learning Research, 2006


Learning Coordinate Covariances via Gradients
Sayan Mukherjee and Ding-xuan Zhou
Journal of Machine Learning Research, 2006


Estimation of Gradients and Coordinate Covariation in Classification
Sayan Mukherjee and Qiang Wu
Journal of Machine Learning Research, 2006


On Representing and Generating Kernels by Fuzzy Equivalence Relations
Bernhard Moser
Journal of Machine Learning Research, 2006


Universal Kernels
Charles A. Micchelli, Yuesheng Xu and Haizhang Zhang
Journal of Machine Learning Research, 2006


Quantile Regression Forests
Nicolai Meinshausen
Journal of Machine Learning Research, 2006


Bounds for Linear Multi-Task Learning
Andreas Maurer
Journal of Machine Learning Research, 2006


Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Olvi L. Mangasarian
Journal of Machine Learning Research, 2006


Walk-Sums and Belief Propagation in Gaussian Graphical Models
Dmitry M. Malioutov, Jason K. Johnson and Alan S. Willsky
Journal of Machine Learning Research, 2006


New Algorithms for Efficient High-Dimensional Nonparametric Classification
Ting Liu, Andrew W. Moore and Alexander G. Gray
Journal of Machine Learning Research, 2006


Infinite-sigma Limits For Tikhonov Regularization
Ross A. Lippert and Ryan M. Rifkin
Journal of Machine Learning Research, 2006


Lower Bounds and Aggregation in Density Estimation
Guillaume Lecué
Journal of Machine Learning Research, 2006


Incremental Support Vector Learning: Analysis, Implementation and Applications
Pavel Laskov, Christian Gehl, Stefan Krüger and Klaus-robert Müller
Journal of Machine Learning Research, 2006


Learning Recursive Control Programs from Problem Solving
Pat Langley and Dongkyu Choi
Journal of Machine Learning Research, 2006


Learning to Detect and Classify Malicious Executables in the Wild
Jeremy Z. Kolter and Marcus A. Maloof
Journal of Machine Learning Research, 2006


Collaborative Multiagent Reinforcement Learning by Payoff Propagation
Jelle R. Kok and Nikos A. Vlassis
Journal of Machine Learning Research, 2006


Toward Attribute Efficient Learning of Decision Lists and Parities
Adam R. Klivans and Rocco A. Servedio
Journal of Machine Learning Research, 2006


Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach
Emanuel Kitzelmann and Ute Schmid
Journal of Machine Learning Research, 2006


Segmental Hidden Markov Models with Random Effects for Waveform Modeling
Seyoung Kim and Padhraic Smyth
Journal of Machine Learning Research, 2006


Building Support Vector Machines with Reduced Classifier Complexity
S. S. Keerthi, Olivier Chapelle and Dennis Decoste
Journal of Machine Learning Research, 2006


Distance Patterns in Structural Similarity
Thomas Kämpke
Journal of Machine Learning Research, 2006


Causal Graph Based Decomposition of Factored MDPs
Anders Jonsson and Andrew G. Barto
Journal of Machine Learning Research, 2006


QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
Don R. Hush, Patrick Kelly, Clint Scovel and Ingo Steinwart
Journal of Machine Learning Research, 2006


Generalized Bradley-Terry Models and Multi-Class Probability Estimates
Tzu-kuo Huang, Ruby C. Weng and Chih-jen Lin
Journal of Machine Learning Research, 2006


Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
Matthias Heiler and Christoph Schnörr
Journal of Machine Learning Research, 2006


Using Machine Learning to Guide Architecture Simulation
Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder and Timothy Sherwood
Journal of Machine Learning Research, 2006


Some Discriminant-Based PAC Algorithms
Paul W. Goldberg
Journal of Machine Learning Research, 2006


Maximum-Gain Working Set Selection for SVMs
Tobias Glasmachers and Christian Igel
Journal of Machine Learning Research, 2006


One-Class Novelty Detection for Seizure Analysis from Intracranial EEG
Andrew B. Gardner, Abba M. Krieger, George J. Vachtsevanos and Brian Litt
Journal of Machine Learning Research, 2006


Spam Filtering Based On The Analysis Of Text Information Embedded Into Images
Giorgio Fumera, Ignazio Pillai and Fabio Roli
Journal of Machine Learning Research, 2006


Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems
Eyal Even-dar, Shie Mannor and Yishay Mansour
Journal of Machine Learning Research, 2006


Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation
Magnus Ekdahl and Timo Koski
Journal of Machine Learning Research, 2006


Statistical Comparisons of Classifiers over Multiple Data Sets
Janez Demsar
Journal of Machine Learning Research, 2006


Online Passive-Aggressive Algorithms
Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-shwartz and Yoram Singer
Journal of Machine Learning Research, 2006


Large Scale Transductive SVMs
Ronan Collobert, Fabian H. Sinz, Jason Weston and Léon Bottou
Journal of Machine Learning Research, 2006


Rearrangement Clustering: Pitfalls, Remedies, and Applications
Sharlee Climer and Weixiong Zhang
Journal of Machine Learning Research, 2006


Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
Di-rong Chen and Tao Sun
Journal of Machine Learning Research, 2006


Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
Fu Chang, Chin-chin Lin and Chi-jen Lu
Journal of Machine Learning Research, 2006


Machine Learning for Computer Security
Philip K. Chan and Richard Lippmann
Journal of Machine Learning Research, 2006


Worst-Case Analysis of Selective Sampling for Linear Classification
Nicolò Cesa-bianchi, Claudio Gentile and Luca Zaniboni
Journal of Machine Learning Research, 2006


Incremental Algorithms for Hierarchical Classification
Nicolò Cesa-bianchi, Claudio Gentile and Luca Zaniboni
Journal of Machine Learning Research, 2006


Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
Tonatiuh P. Centeno and Neil D. Lawrence
Journal of Machine Learning Research, 2006


A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
Enrique F. Castillo, Bertha Guijarro-berdiñas, Oscar Fontenla-romero and Amparo Alonso-betanzos
Journal of Machine Learning Research, 2006


A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With {\it p} Larger Than {\it n}
Robert Castelo and Alberto Roverato
Journal of Machine Learning Research, 2006


Stability Properties of Empirical Risk Minimization over Donsker Classes
Andrea Caponnetto and Alexander Rakhlin
Journal of Machine Learning Research, 2006


A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests
Luis Campos
Journal of Machine Learning Research, 2006


Sparse Boosting
Peter Bühlmann and Bin Yu
Journal of Machine Learning Research, 2006


Accurate Error Bounds for the Eigenvalues of the Kernel Matrix
Mikio L. Braun
Journal of Machine Learning Research, 2006


Spam Filtering Using Statistical Data Compression Models
Andrej Bratko, Gordon V. Cormack, Bogdan Filipic, Thomas R. Lynam and Blaz Zupan
Journal of Machine Learning Research, 2006


In Search of Non-Gaussian Components of a High-Dimensional Distribution
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny and Klaus-robert Müller
Journal of Machine Learning Research, 2006


Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem
Tijl D. Bie and Nello Cristianini
Journal of Machine Learning Research, 2006


Some Theory for Generalized Boosting Algorithms
Peter J. Bickel, Yaacov Ritov and Alon Zakai
Journal of Machine Learning Research, 2006


A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events
Shalabh Bhatnagar, Vivek S. Borkar and Madhukar Akarapu
Journal of Machine Learning Research, 2006


Linear Programs for Hypotheses Selection in Probabilistic Inference Models
Anders Bergkvist, Peter Damaschke and Marcel Lüthi
Journal of Machine Learning Research, 2006


The Interplay of Optimization and Machine Learning Research
Kristin P. Bennett and Emilio Parrado-hernández
Journal of Machine Learning Research, 2006


Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
Mikhail Belkin, Partha Niyogi and Vikas Sindhwani
Journal of Machine Learning Research, 2006


Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition
Ron Begleiter and Ran El-yaniv
Journal of Machine Learning Research, 2006


Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems
David Barber
Journal of Machine Learning Research, 2006


Learning Spectral Clustering, With Application To Speech Separation
Francis R. Bach and Michael I. Jordan
Journal of Machine Learning Research, 2006


Considering Cost Asymmetry in Learning Classifiers
Francis R. Bach, David Heckerman and Eric Horvitz
Journal of Machine Learning Research, 2006


Learning a Hidden Hypergraph
Dana Angluin and Jiang Chen
Journal of Machine Learning Research, 2006


Learning Factor Graphs in Polynomial Time and Sample Complexity
Pieter Abbeel, Daphne Koller and Andrew Y. Ng
Journal of Machine Learning Research, 2006


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


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


A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation
Andreas Ziehe, Pavel Laskov, Guido Nolte and Klaus-robert Müller
Journal of Machine Learning Research, 2004


Statistical Analysis of Some Multi-Category Large Margin Classification Methods
Tong Zhang
Journal of Machine Learning Research, 2004


Hierarchical Latent Class Models for Cluster Analysis
Nevin L. Zhang
Journal of Machine Learning Research, 2004


Efficient Feature Selection via Analysis of Relevance and Redundancy
Lei Yu and Huan Liu
Journal of Machine Learning Research, 2004


Probability Estimates for Multi-class Classification by Pairwise Coupling
Ting-fan Wu, Chih-jen Lin and Ruby C. Weng
Journal of Machine Learning Research, 2004


A Universal Well-Calibrated Algorithm for On-line Classification
Vladimir Vovk
Journal of Machine Learning Research, 2004


Some Properties of Regularized Kernel Methods
Ernesto D. Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana and Alessandro Verri
Journal of Machine Learning Research, 2004


Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
Giorgio Valentini and Thomas G. Dietterich
Journal of Machine Learning Research, 2004


Randomized Variable Elimination
David J. Stracuzzi and Paul E. Utgoff
Journal of Machine Learning Research, 2004


Some Dichotomy Theorems for Neural Learning Problems
Michael Schmitt
Journal of Machine Learning Research, 2004


Reinforcement Learning with Factored States and Actions
Brian Sallans and Geoffrey E. Hinton
Journal of Machine Learning Research, 2004


The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins
Cynthia Rudin, Ingrid Daubechies and Robert E. Schapire
Journal of Machine Learning Research, 2004


Boosting as a Regularized Path to a Maximum Margin Classifier
Saharon Rosset, Ji Zhu and Trevor Hastie
Journal of Machine Learning Research, 2004


In Defense of One-Vs-All Classification
Ryan M. Rifkin and Aldebaro Klautau
Journal of Machine Learning Research, 2004


Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces
Michael Quist and Golan Yona
Journal of Machine Learning Research, 2004


On the Importance of Small Coordinate Projections
Shahar Mendelson and Petra Philips
Journal of Machine Learning Research, 2004


The Sample Complexity of Exploration in the Multi-Armed Bandit Problem
Shie Mannor and John N. Tsitsiklis
Journal of Machine Learning Research, 2004


A Geometric Approach to Multi-Criterion Reinforcement Learning
Shie Mannor and Nahum Shimkin
Journal of Machine Learning Research, 2004


Knowledge-Based Kernel Approximation
Olvi L. Mangasarian, Jude W. Shavlik and Edward W. Wild
Journal of Machine Learning Research, 2004


A Compression Approach to Support Vector Model Selection
Ulrike V. Luxburg, Olivier Bousquet and Bernhard Schölkopf
Journal of Machine Learning Research, 2004


Distance-Based Classification with Lipschitz Functions
Ulrike V. Luxburg and Olivier Bousquet
Journal of Machine Learning Research, 2004


RCV1: A New Benchmark Collection for Text Categorization Research
David D. Lewis, Yiming Yang, Tony G. Rose and Fan Li
Journal of Machine Learning Research, 2004


Fast String Kernels using Inexact Matching for Protein Sequences
Christina S. Leslie and Rui Kuang
Journal of Machine Learning Research, 2004


Lossless Online Bayesian Bagging
Herbert Lee and Merlise A. Clyde
Journal of Machine Learning Research, 2004


Subgroup Discovery with CN2-SD
Nada Lavrac, Branko Kavsek, Peter A. Flach and Ljupco Todorovski
Journal of Machine Learning Research, 2004


Feature Discovery in Non-Metric Pairwise Data
Julian Laub and Klaus-robert Müller
Journal of Machine Learning Research, 2004


Computable Shell Decomposition Bounds
John Langford and David A. Mcallester
Journal of Machine Learning Research, 2004


Learning the Kernel Matrix with Semidefinite Programming
Gert Lanckriet, Nello Cristianini, Peter L. Bartlett, Laurent E. Ghaoui and Michael I. Jordan
Journal of Machine Learning Research, 2004


Exact Bayesian Structure Discovery in Bayesian Networks
Mikko Koivisto and Kismat Sood
Journal of Machine Learning Research, 2004


Sources of Success for Boosted Wrapper Induction
David Kauchak, Joseph Smarr and Charles Elkan
Journal of Machine Learning Research, 2004


Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees
Matti Kääriäinen, Tuomo Malinen and Tapio Elomaa
Journal of Machine Learning Research, 2004


Probability Product Kernels
Tony Jebara, Risi Kondor and Andrew Howard
Journal of Machine Learning Research, 2004


The Minimum Error Minimax Probability Machine
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu and Laiwan Chan
Journal of Machine Learning Research, 2004


Non-negative Matrix Factorization with Sparseness Constraints
Patrik O. Hoyer
Journal of Machine Learning Research, 2004


Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters
Isao Higuchi and Shinto Eguchi
Journal of Machine Learning Research, 2004


The Entire Regularization Path for the Support Vector Machine
Trevor Hastie, Saharon Rosset, Robert Tibshirani and Ji Zhu
Journal of Machine Learning Research, 2004


Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Evan Greensmith, Peter L. Bartlett and Jonathan Baxter
Journal of Machine Learning Research, 2004


New Techniques for Disambiguation in Natural Language and Their Application to Biological Text
Filip Ginter, Jorma Boberg, Jouni Järvinen and Tapio Salakoski
Journal of Machine Learning Research, 2004


Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
Kenji Fukumizu, Francis R. Bach and Michael I. Jordan
Journal of Machine Learning Research, 2004


Fast Binary Feature Selection with Conditional Mutual Information
Françcois Fleuret
Journal of Machine Learning Research, 2004


Feature Selection for Unsupervised Learning
Jennifer G. Dy and Carla E. Brodley
Journal of Machine Learning Research, 2004


Model Averaging for Prediction with Discrete Bayesian Networks
Denver Dash and Gregory F. Cooper
Journal of Machine Learning Research, 2004


Rational Kernels: Theory and Algorithms
Corinna Cortes, Patrick Haffner and Mehryar Mohri
Journal of Machine Learning Research, 2004


PAC-learnability of Probabilistic Deterministic Finite State Automata
Alexander Clark and Franck Thollard
Journal of Machine Learning Research, 2004


On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition
Andreas Christmann and Ingo Steinwart
Journal of Machine Learning Research, 2004


Large-Sample Learning of Bayesian Networks is NP-Hard
David M. Chickering, David Heckerman and Christopher Meek
Journal of Machine Learning Research, 2004


Support Vector Machine Soft Margin Classifiers: Error Analysis
Di-rong Chen, Qiang Wu, Yiming Ying and Ding-xuan Zhou
Journal of Machine Learning Research, 2004


Image Categorization by Learning and Reasoning with Regions
Yixin Chen and James Z. Wang
Journal of Machine Learning Research, 2004


Learning Ensembles from Bites: A Scalable and Accurate Approach
Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer and W. P. Kegelmeyer
Journal of Machine Learning Research, 2004


Preference Elicitation and Query Learning
Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm and Martin Zinkevich
Journal of Machine Learning Research, 2004


Second Order Cone Programming Formulations for Feature Selection
Chiranjib Bhattacharyya
Journal of Machine Learning Research, 2004


No Unbiased Estimator of the Variance of K-Fold Cross-Validation
Yoshua Bengio and Yves Grandvalet
Journal of Machine Learning Research, 2004


Weather Data Mining Using Independent Component Analysis
Jayanta Basak, Anant Sudarshan, Deepak Trivedi and M. S. Santhanam
Journal of Machine Learning Research, 2004


Online Choice of Active Learning Algorithms
Yoram Baram, Ran El-yaniv and Kobi Luz
Journal of Machine Learning Research, 2004


Generalization Error Bounds for Threshold Decision Lists
Martin Anthony
Journal of Machine Learning Research, 2004


Tree-Structured Neural Decoding
Christian D'avignon and Donald Geman
Journal of Machine Learning Research, 2003


Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation
Andreas Ziehe, Motoaki Kawanabe, Stefan Harmeling and Klaus-robert Müller
Journal of Machine Learning Research, 2003


A Unified Framework for Model-based Clustering
Shi Zhong and Joydeep Ghosh
Journal of Machine Learning Research, 2003


Kernel Methods for Relation Extraction
Dmitry Zelenko, Chinatsu Aone and Anthony Richardella
Journal of Machine Learning Research, 2003


Learning over Sets using Kernel Principal Angles
Lior Wolf and Amnon Shashua
Journal of Machine Learning Research, 2003


Use of the Zero-Norm with Linear Models and Kernel Methods
Jason Weston, André Elisseeff, Bernhard Schölkopf and Michael E. Tipping
Journal of Machine Learning Research, 2003


Blind Source Recovery: A Framework in the State Space
Khurram Waheed and Fathi M. Salem
Journal of Machine Learning Research, 2003


The em Algorithm for Kernel Matrix Completion with Auxiliary Data
Koji Tsuda, Shotaro Akaho and Kiyoshi Asai
Journal of Machine Learning Research, 2003


Feature Extraction by Non-Parametric Mutual Information Maximization
Kari Torkkola
Journal of Machine Learning Research, 2003


Energy-Based Models for Sparse Overcomplete Representations
Yee W. Teh, Max Welling, Simon Osindero and Geoffrey E. Hinton
Journal of Machine Learning Research, 2003


Path Kernels and Multiplicative Updates
Eiji Takimoto and Manfred K. Warmuth
Journal of Machine Learning Research, 2003


Ranking a Random Feature for Variable and Feature Selection
Hervé Stoppiglia, Gérard Dreyfus, Rémi Dubois and Yacine Oussar
Journal of Machine Learning Research, 2003


Sparseness of Support Vector Machines
Ingo Steinwart
Journal of Machine Learning Research, 2003


A Generative Model for Separating Illumination and Reflectance from Images
Inna Stainvas and David Lowe
Journal of Machine Learning Research, 2003


An Empirical Study of the Use of Relevance Information in Inductive Logic Programming
Ashwin Srinivasan, Ross D. King and Michael Bain
Journal of Machine Learning Research, 2003


Smooth Boosting and Learning with Malicious Noise
Rocco A. Servedio
Journal of Machine Learning Research, 2003


Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifold
Lawrence K. Saul and Sam T. Roweis
Journal of Machine Learning Research, 2003


Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions
Jaakko Särelä and Ricardo Vigário
Journal of Machine Learning Research, 2003


MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling
Isabelle Rivals and Léon Personnaz
Journal of Machine Learning Research, 2003


Overfitting in Making Comparisons Between Variable Selection Methods
Juha Reunanen
Journal of Machine Learning Research, 2003


Variable Selection Using SVM-based Criteria
Alain Rakotomamonjy
Journal of Machine Learning Research, 2003


FINkNN: A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples
Vassilios Petridis and Vassilis G. Kaburlasos
Journal of Machine Learning Research, 2003


Tree Induction vs. Logistic Regression: A Learning-Curve Analysis
Claudia Perlich, Foster J. Provost and Jeffrey S. Simonoff
Journal of Machine Learning Research, 2003


Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space
Simon Perkins, Kevin Lacker and James Theiler
Journal of Machine Learning Research, 2003


Blind Source Separation via Generalized Eigenvalue Decomposition
Lucas C. Parra and Paul Sajda
Journal of Machine Learning Research, 2003


ILP: A Short Look Back and a Longer Look Forward
David Page and Ashwin Srinivasan
Journal of Machine Learning Research, 2003


Tracking Linear-threshold Concepts with Winnow
Chris Mesterharm
Journal of Machine Learning Research, 2003


On the Performance of Kernel Classes
Shahar Mendelson
Journal of Machine Learning Research, 2003


Generalization Error Bounds for Bayesian Mixture Algorithms
Ron Meir and Tong Zhang
Journal of Machine Learning Research, 2003


Concentration Inequalities for the Missing Mass and for Histogram Rule Error
David A. Mcallester and Luis E. Ortiz
Journal of Machine Learning Research, 2003


Speedup Learning for Repair-based Search by Identifying Redundant Steps
Shaul Markovitch and Asaf Shatil
Journal of Machine Learning Research, 2003


Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity
Shie Mannor, Ron Meir and Tong Zhang
Journal of Machine Learning Research, 2003


An Approximate Analytical Approach to Resampling Averages
Dörthe Malzahn and Manfred Opper
Journal of Machine Learning Research, 2003


Introduction to Special Issue on Independent Components Analysis
Te-won Lee, Jean-françcois Cardoso, Erkki Oja and Shun-ichi Amari
Journal of Machine Learning Research, 2003


ICA Using Spacings Estimates of Entropy
Erik G. Learned-miller and John Iii
Journal of Machine Learning Research, 2003


Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains
Helge Langseth and Thomas D. Nielsen
Journal of Machine Learning Research, 2003


Least-Squares Policy Iteration
Michail G. Lagoudakis and Ronald Parr
Journal of Machine Learning Research, 2003


On Nearest-Neighbor Error-Correcting Output Codes with Application to All-Pairs Multiclass Support Vector Machines
Aldebaro Klautau, Nikola Jevtic and Alon Orlitsky
Journal of Machine Learning Research, 2003


A Multiscale Framework For Blind Separation of Linearly Mixed Signals
Pavel Kisilev, Michael Zibulevsky and Yehoshua Y. Zeevi
Journal of Machine Learning Research, 2003


A Maximum Likelihood Approach to Single-channel Source Separation
Gil-jin Jang and Te-won Lee
Journal of Machine Learning Research, 2003


Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet
Marcus Hutter
Journal of Machine Learning Research, 2003


Nash Q-Learning for General-Sum Stochastic Games
Junling Hu and Michael P. Wellman
Journal of Machine Learning Research, 2003


Introduction to the Special Issue on Learning Theory
Ralf Herbrich and Thore Graepel
Journal of Machine Learning Research, 2003


Preference Elicitation via Theory Refinement
Peter Haddawy, Vu A. Ha, Angelo C. Restificar, Benjamin Geisler and John Miyamoto
Journal of Machine Learning Research, 2003


An Introduction to Variable and Feature Selection
Isabelle Guyon and André Elisseeff
Journal of Machine Learning Research, 2003


Sufficient Dimensionality Reduction
Amir Globerson and Naftali Tishby
Journal of Machine Learning Research, 2003


Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
Dmitry Gavinsky
Journal of Machine Learning Research, 2003


Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task
Sandra C. Gadanho
Journal of Machine Learning Research, 2003


Learning Probabilistic Models: An Expected Utility Maximization Approach
Craig Friedman and Sven Sandow
Journal of Machine Learning Research, 2003


An Efficient Boosting Algorithm for Combining Preferences
Yoav Freund, Raj D. Iyer, Robert E. Schapire and Yoram Singer
Journal of Machine Learning Research, 2003


An Extensive Empirical Study of Feature Selection Metrics for Text Classification
George Forman
Journal of Machine Learning Research, 2003


Learning Rates for Q-learning
Eyal Even-dar and Yishay Mansour
Journal of Machine Learning Research, 2003


Combining Knowledge from Different Sources in Causal Probabilistic Models
Marek J. Druzdzel and Francisco J. D\'ıez
Journal of Machine Learning Research, 2003


A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification
Inderjit S. Dhillon, Subramanyam Mallela and Rahul Kumar
Journal of Machine Learning Research, 2003


A Family of Additive Online Algorithms for Category Ranking
Koby Crammer and Yoram Singer
Journal of Machine Learning Research, 2003


Ultraconservative Online Algorithms for Multiclass Problems
Koby Crammer and Yoram Singer
Journal of Machine Learning Research, 2003


Query Transformations for Improving the Efficiency of ILP Systems
V\'ıtor S. Costa, Ashwin Srinivasan, Rui Camacho, Hendrik Blockeel, Bart Demoen, Gerda Janssens, Jan Struyf, Henk Vandecasteele and Wim V. Laer
Journal of Machine Learning Research, 2003


Learning Semantic Lexicons from a Part-of-Speech and Semantically Tagged Corpus Using Inductive Logic Programming
Vincent Claveau, Pascale Sébillot, Cécile Fabre and Pierrette Bouillon
Journal of Machine Learning Research, 2003


Comparing Bayes Model Averaging and Stacking When Model Approximation Error Cannot be Ignored
Bertrand Clarke
Journal of Machine Learning Research, 2003


Inducing Grammars from Sparse Data Sets: A Survey of Algorithms and Results
Orlando Cicchello and Stefan C. Kremer
Journal of Machine Learning Research, 2003


Designing Committees of Models through Deliberate Weighting of Data Points
Stefan W. Christensen, Ian Sinclair and Philippa Reed
Journal of Machine Learning Research, 2003


On Inclusion-Driven Learning of Bayesian Networks
Robert Castelo and Tomás Kocka
Journal of Machine Learning Research, 2003


Benefitting from the Variables that Variable Selection Discards
Rich Caruana and Virginia Sa
Journal of Machine Learning Research, 2003


Dependence, Correlation and Gaussianity in Independent Component Analysis
Jean-françcois Cardoso
Journal of Machine Learning Research, 2003


Word-Sequence Kernels
Nicola Cancedda, Éric Gaussier, Cyril Goutte and Jean-michel Renders
Journal of Machine Learning Research, 2003


Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction
Mary E. Califf and Raymond J. Mooney
Journal of Machine Learning Research, 2003


On the Proper Learning of Axis-Parallel Concepts
Nader H. Bshouty and Lynn Burroughs
Journal of Machine Learning Research, 2003


ICA for Watermarking Digital Images
Stéphane Bounkong, Borémi Toch, David Saad and David Lowe
Journal of Machine Learning Research, 2003


Relational Learning as Search in a Critical Region
Marco Botta, Attilio Giordana, Lorenza Saitta and Mich\`ele Sebag
Journal of Machine Learning Research, 2003


Latent Dirichlet Allocation
David M. Blei, Andrew Y. Ng and Michael I. Jordan
Journal of Machine Learning Research, 2003


On the Rate of Convergence of Regularized Boosting Classifiers
Gilles Blanchard, Gábor Lugosi and Nicolas Vayatis
Journal of Machine Learning Research, 2003


Dimensionality Reduction via Sparse Support Vector Machines
Jinbo Bi, Kristin P. Bennett, Mark J. Embrechts, Curt M. Breneman and Minghu Song
Journal of Machine Learning Research, 2003


A Neural Probabilistic Language Model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent and Christian Janvin
Journal of Machine Learning Research, 2003


Extensions to Metric-Based Model Selection
Yoshua Bengio and Nicolas Chapados
Journal of Machine Learning Research, 2003


Distributional Word Clusters vs. Words for Text Categorization
Ron Bekkerman, Ran El-yaniv, Naftali Tishby and Yoad Winter
Journal of Machine Learning Research, 2003


Statistical Dynamics of On-line Independent Component Analysis
Gleb Basalyga and Magnus Rattray
Journal of Machine Learning Research, 2003


Matching Words and Pictures
Kobus Barnard, Pinar Duygulu, David A. Forsyth, Nando D. Freitas, David M. Blei and Michael I. Jordan
Journal of Machine Learning Research, 2003


The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem
Pierre Baldi and Gianluca Pollastri
Journal of Machine Learning Research, 2003


Task Clustering and Gating for Bayesian Multitask Learning
Bart Bakker and Tom Heskes
Journal of Machine Learning Research, 2003


Beyond Independent Components: Trees and Clusters
Francis R. Bach and Michael I. Jordan
Journal of Machine Learning Research, 2003


MISEP -- Linear and Nonlinear ICA Based on Mutual Information
Luis B. Almeida
Journal of Machine Learning Research, 2003


Recommender Systems Using Linear Classifier
Tong Zhang and Vijay S. Iyengar
Journal of Machine Learning Research, 2002


Text Chunking based on a Generalization of Winnow
Tong Zhang, Fred Damerau and David Johnson
Journal of Machine Learning Research, 2002


Covering Number Bounds of Certain Regularized Linear Function Classes
Tong Zhang
Journal of Machine Learning Research, 2002


On the Convergence of Optimistic Policy Iteration
John N. Tsitsiklis
Journal of Machine Learning Research, 2002


MDPs: Learning in Varying Environments
Istvan Szita, Bálint Takács and András Lörincz
Journal of Machine Learning Research, 2002


The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
Masashi Sugiyama and Klaus-robert Müller
Journal of Machine Learning Research, 2002


Policy Search using Paired Comparisons
Malcolm Strens and Andrew W. Moore
Journal of Machine Learning Research, 2002


Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions
Alexander Strehl and Joydeep Ghosh
Journal of Machine Learning Research, 2002


Learning to Construct Fast Signal Processing Implementations
Bryan Singer and Manuela M. Veloso
Journal of Machine Learning Research, 2002


PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Matthias Seeger
Journal of Machine Learning Research, 2002


Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem
Marc Sebban, Richard Nock and Stéphane Lallich
Journal of Machine Learning Research, 2002


Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling
Tobias Scheffer and Stefan Wrobel
Journal of Machine Learning Research, 2002


Memory-Based Shallow Parsing
Erik Sang
Journal of Machine Learning Research, 2002


Lyapunov Design for Safe Reinforcement Learning
Theodore J. Perkins and Andrew G. Barto
Journal of Machine Learning Research, 2002


Shallow Parsing using Noisy and Non-Stationary Training Material
Miles Osborne
Journal of Machine Learning Research, 2002


On Online Learning of Decision Lists
Ziv Nevo and Ran El-yaniv
Journal of Machine Learning Research, 2002


Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
Prasanth B. Nair, Arindam Choudhury and Andy J. Keane
Journal of Machine Learning Research, 2002


Shallow Parsing using Specialized HMMs
Antonio Molina and Ferran Pla
Journal of Machine Learning Research, 2002


Shallow Parsing with PoS Taggers and Linguistic Features
Beáta Megyesi
Journal of Machine Learning Research, 2002


The Learning-Curve Sampling Method Applied to Model-Based Clustering
Christopher Meek, Bo Thiesson and David Heckerman
Journal of Machine Learning Research, 2002


Coupled Clustering: A Method for Detecting Structural Correspondence
Zvika Marx, Ido Dagan, Joachim M. Buhmann and Eli Shamir
Journal of Machine Learning Research, 2002


The Set Covering Machine
Mario Marchand and John Shawe-taylor
Journal of Machine Learning Research, 2002


Text Classification using String Kernels
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini and Christopher Watkins
Journal of Machine Learning Research, 2002


The Representational Power of Discrete Bayesian Networks
Charles X. Ling and Huajie Zhang
Journal of Machine Learning Research, 2002


A Robust Minimax Approach to Classification
Gert Lanckriet, Laurent E. Ghaoui, Chiranjib Bhattacharyya and Michael I. Jordan
Journal of Machine Learning Research, 2002


Efficient Algorithms for Universal Portfolios
Adam Kalai and Santosh Vempala
Journal of Machine Learning Research, 2002


Algorithmic Luckiness
Ralf Herbrich and Robert C. Williamson
Journal of Machine Learning Research, 2002


Introduction to Special Issue on Machine Learning Approaches to Shallow Parsing
James Hammerton, Miles Osborne, Susan Armstrong and Walter Daelemans
Journal of Machine Learning Research, 2002


Learning Probabilistic Models of Link Structure
Lise Getoor, Nir Friedman, Daphne Koller and Benjamin Taskar
Journal of Machine Learning Research, 2002


Learning Precise Timing with LSTM Recurrent Networks
Felix A. Gers, Nicol N. Schraudolph and Jürgen Schmidhuber
Journal of Machine Learning Research, 2002


Round Robin Classification
Johannes Fürnkranz
Journal of Machine Learning Research, 2002


Minimal Kernel Classifiers
Glenn Fung, Olvi L. Mangasarian and Alex J. Smola
Journal of Machine Learning Research, 2002


Multiple-Instance Learning of Real-Valued Data
Daniel R. Dooly, Qi Zhang, Sally A. Goldman and Robert A. Amar
Journal of Machine Learning Research, 2002


Learning Rules and Their Exceptions
Hervé Déjean
Journal of Machine Learning Research, 2002


Optimal Structure Identification With Greedy Search
David M. Chickering
Journal of Machine Learning Research, 2002


Learning Equivalence Classes of Bayesian-Network Structures
David M. Chickering
Journal of Machine Learning Research, 2002


Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components
Kwokleung Chan, Te-won Lee and Terrence J. Sejnowski
Journal of Machine Learning Research, 2002


Machine Learning with Data Dependent Hypothesis Classes
Adam Cannon, J. M. Ettinger, Don R. Hush and Clint Scovel
Journal of Machine Learning Research, 2002


On Boosting with Polynomially Bounded Distributions
Nader H. Bshouty and Dmitry Gavinsky
Journal of Machine Learning Research, 2002


On Using Extended Statistical Queries to Avoid Membership Queries
Nader H. Bshouty and Vitaly Feldman
Journal of Machine Learning Research, 2002


Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries
Nader H. Bshouty and Nadav Eiron
Journal of Machine Learning Research, 2002


R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
Ronen I. Brafman and Moshe Tennenholtz
Journal of Machine Learning Research, 2002


Tracking a Small Set of Experts by Mixing Past Posteriors
Olivier Bousquet and Manfred K. Warmuth
Journal of Machine Learning Research, 2002


Stability and Generalization
Olivier Bousquet and André Elisseeff
Journal of Machine Learning Research, 2002


Stability and Generalization
Olivier Bousquet and André Elisseeff
Journal of Machine Learning Research, 2002


Efficient Algorithms for Decision Tree Cross-validation
Hendrik Blockeel and Jan Struyf
Journal of Machine Learning Research, 2002


Limitations of Learning Via Embeddings in Euclidean Half Spaces
Shai Ben-david, Nadav Eiron and Hans-ulrich Simon
Journal of Machine Learning Research, 2002


Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
Peter L. Bartlett and Shahar Mendelson
Journal of Machine Learning Research, 2002


Kernel Independent Component Analysis
Francis R. Bach and Michael I. Jordan
Journal of Machine Learning Research, 2002


Using Confidence Bounds for Exploitation-Exploration Trade-offs
Peter Auer
Journal of Machine Learning Research, 2002


Data-dependent margin-based generalization bounds for classification
András Antos, Balázs Kégl, Tamás Linder and Gábor Lugosi
Journal of Machine Learning Research, 2002


Support Vector Machine Active Learning with Applications to Text Classification
Simon Tong and Daphne Koller
Journal of Machine Learning Research, 2001


Sparse Bayesian Learning and the Relevance Vector Machine
Michael E. Tipping
Journal of Machine Learning Research, 2001


Uniform Object Generation for Optimizing One-class Classifiers
David Tax and Robert Duin
Journal of Machine Learning Research, 2001


On the Influence of the Kernel on the Consistency of Support Vector Machines
Ingo Steinwart
Journal of Machine Learning Research, 2001


Regularized Principal Manifolds
Alex J. Smola, Sebastian Mika, Bernhard Schölkopf and Robert C. Williamson
Journal of Machine Learning Research, 2001


Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space
Roman Rosipal and Leonard J. Trejo
Journal of Machine Learning Research, 2001


A Generalized Kernel Approach to Dissimilarity-based Classification
Elzbieta Pekalska, Pavel Pacl\'ık and Robert Duin
Journal of Machine Learning Research, 2001


On the Size of Convex Hulls of Small Sets
Shahar Mendelson
Journal of Machine Learning Research, 2001


Lagrangian Support Vector Machines
Olvi L. Mangasarian and David R. Musicant
Journal of Machine Learning Research, 2001


One-Class SVMs for Document Classification
Larry M. Manevitz and Malik Yousef
Journal of Machine Learning Research, 2001


Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms
Robert E. Mahony and Robert C. Williamson
Journal of Machine Learning Research, 2001


Graph-Based Hierarchical Conceptual Clustering
Istvan Jonyer, Diane J. Cook and Lawrence B. Holder
Journal of Machine Learning Research, 2001


Tracking the Best Linear Predictor
Mark Herbster and Manfred K. Warmuth
Journal of Machine Learning Research, 2001


Bayes Point Machines
Ralf Herbrich, Thore Graepel and Colin Campbell
Journal of Machine Learning Research, 2001


Classes of Kernels for Machine Learning: A Statistics Perspective
Marc G. Genton
Journal of Machine Learning Research, 2001


A New Approximate Maximal Margin Classification Algorithm
Claudio Gentile
Journal of Machine Learning Research, 2001


Efficient SVM Training Using Low-Rank Kernel Representations
Shai Fine and Katya Scheinberg
Journal of Machine Learning Research, 2001


Exact Simplification of Support Vector Solutions
Tom Downs, Kevin E. Gates and Annette Masters
Journal of Machine Learning Research, 2001


On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines
Koby Crammer and Yoram Singer
Journal of Machine Learning Research, 2001


SVMTorch: Support Vector Machines for Large-Scale Regression Problems
Ronan Collobert and Samy Bengio
Journal of Machine Learning Research, 2001


Support Vector Clustering
Asa Ben-hur, David Horn, Hava T. Siegelmann and Vladimir Vapnik
Journal of Machine Learning Research, 2001


Learning with Mixtures of Trees
Marina Meila and Michael I. Jordan
Journal of Machine Learning Research, 2000


Dependency Networks for Inference, Collaborative Filtering, and Data Visualization
David Heckerman, David M. Chickering, Christopher Meek, Robert Rounthwaite and Carl M. Kadie
Journal of Machine Learning Research, 2000


Learning Evaluation Functions to Improve Optimization by Local Search
Justin A. Boyan and Andrew W. Moore
Journal of Machine Learning Research, 2000


Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
Erin L. Allwein, Robert E. Schapire and Yoram Singer
Journal of Machine Learning Research, 2000