JMLR Volume 9

Max-margin Classification of Data with Absent Features: Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller; 9(Jan):1--21, 2008.
[abs][pdf]

Linear-Time Computation of Similarity Measures for Sequential Data: Konrad Rieck, Pavel Laskov; 9(Jan):23--48, 2008.
[abs][pdf]

On the Suitable Domain for SVM Training in Image Coding: Gustavo Camps-Valls, Juan Gutiérrez, Gabriel Gómez-Pérez, Jesús Malo; 9(Jan):49--66, 2008.
[abs][pdf]

Discriminative Learning of Max-Sum Classifiers: Vojtěch Franc, Bogdan Savchynskyy; 9(Jan):67--104, 2008.
[abs][pdf]

Active Learning by Spherical Subdivision: Falk-Florian Henrich, Klaus Obermayer; 9(Jan):105--130, 2008.
[abs][pdf]

Evidence Contrary to the Statistical View of Boosting: David Mease, Abraham Wyner; 9(Feb):131--156, 2008.
[abs][pdf] [pdf with discussion]

Responses to Evidence Contrary to the Statistical View of Boosting: Kristin P. Bennett; 9(Feb):175--164, 2008. [pdf]; Andreas Buja, Werner Stuetzle; 9(Feb):165--170, 2008. [pdf]; Yoav Freund, Robert E. Schapire; 9(Feb):171--174, 2008. [pdf]; Jerome Friedman, Trevor Hastie, Robert Tibshirani; 9(Feb):175--180, 2008. [pdf]; Peter J. Bickel, Ya'acov Ritov; 9(Feb):181--186, 2008. [pdf]; Peter Bühlmann, Bin Yu; 9(Feb):187--194, 2008. [pdf]

Rejoinder to Reponses to Evidence Contrary to the Statistical View of Boosting: David Mease, Abraham Wyner; 9(Feb):195--201, 2008. [pdf]

Optimization Techniques for Semi-Supervised Support Vector Machines: Olivier Chapelle, Vikas Sindhwani, Sathiya S. Keerthi; 9(Feb):203--233, 2008.
[abs][pdf]

Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies: Andreas Krause, Ajit Singh, Carlos Guestrin; 9(Feb):235--284, 2008.
[abs][pdf]

Support Vector Machinery for Infinite Ensemble Learning: Hsuan-Tien Lin, Ling Li; 9(Feb):285--312, 2008.
[abs][pdf]

Algorithms for Sparse Linear Classifiers in the Massive Data Setting: Suhrid Balakrishnan, David Madigan; 9(Feb):313--337, 2008.
[abs][pdf]

Generalization from Observed to Unobserved Features by Clustering: Eyal Krupka, Naftali Tishby; 9(Mar):339--370, 2008.
[abs][pdf]

A Tutorial on Conformal Prediction: Glenn Shafer, Vladimir Vovk; 9(Mar):371--421, 2008.
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Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective: Liviu Panait, Karl Tuyls, Sean Luke; 9(Mar):423--457, 2008.
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A Recursive Method for Structural Learning of Directed Acyclic Graphs: Xianchao Xie, Zhi Geng; 9(Mar):459--483, 2008.
[abs][pdf]

Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data: Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont; 9(Mar):485--516, 2008.
[abs][pdf]

Comments on the Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion: Jieping Ye; 9(Mar):517--519, 2008.
[abs][pdf]

Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers: Bo Jiang, Xuegong Zhang, Tianxi Cai; 9(Mar):521--540, 2008.
[abs][pdf]

An Information Criterion for Variable Selection in Support Vector Machines (Special Topic on Model Selection): Gerda Claeskens, Christophe Croux, Johan Van Kerckhoven; 9(Mar):541--558, 2008.
[abs][pdf]

Closed Sets for Labeled Data: Gemma C. Garriga, Petra Kralj, Nada Lavrač; 9(Apr):559--580, 2008.
[abs][pdf]

Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2: Giorgio Corani, Marco Zaffalon; 9(Apr):581--621, 2008.
[abs][pdf]

A Library for Locally Weighted Projection Regression (Machine Learning Open Source Software Paper): Stefan Klanke, Sethu Vijayakumar, Stefan Schaal; 9(Apr):623--626, 2008.
[abs][pdf] [code][mloss.org]

Trust Region Newton Method for Logistic Regression: Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi; 9(Apr):627--650, 2008.
[abs][pdf]

Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns: Shann-Ching Chen, Geoffrey J. Gordon, Robert F. Murphy; 9(Apr):651--682, 2008.
[abs][pdf]

Learning Control Knowledge for Forward Search Planning: Sungwook Yoon, Alan Fern, Robert Givan; 9(Apr):683--718, 2008.
[abs][pdf]

Multi-class Discriminant Kernel Learning via Convex Programming: Jieping Ye, Shuiwang Ji, Jianhui Chen; 9(Apr):719--758, 2008.
[abs][pdf]

Bayesian Inference and Optimal Design for the Sparse Linear Model: Matthias W. Seeger; 9(Apr):759--813, 2008.
[abs][pdf]

Finite-Time Bounds for Fitted Value Iteration: Rémi Munos, Csaba Szepesvári; 9(May):815--857, 2008.
[abs][pdf]

An Error Bound Based on a Worst Likely Assignment: Eric Bax, Augusto Callejas; 9(May):859--891, 2008.
[abs][pdf]

Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models: Mathias Drton, Thomas S. Richardson; 9(May):893--914, 2008.
[abs][pdf]

Bouligand Derivatives and Robustness of Support Vector Machines for Regression: Andreas Christmann, Arnout Van Messem; 9(May):915--936, 2008.
[abs][pdf]

Accelerated Neural Evolution through Cooperatively Coevolved Synapses: Faustino Gomez, Jürgen Schmidhuber, Risto Miikkulainen; 9(May):937--965, 2008.
[abs][pdf]

Search for Additive Nonlinear Time Series Causal Models: Tianjiao Chu, Clark Glymour; 9(May):967--991, 2008.
[abs][pdf]

Shark (Machine Learning Open Source Software Paper): Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers; 9(Jun):993--996, 2008.
[abs][pdf] [code][mloss.org]

Hit Miss Networks with Applications to Instance Selection: Elena Marchiori; 9(Jun):997--1017, 2008.
[abs][pdf]

Consistency of Trace Norm Minimization: Francis R. Bach; 9(Jun):1019--1048, 2008.
[abs][pdf]

Learning Similarity with Operator-valued Large-margin Classifiers: Andreas Maurer; 9(Jun):1049--1082, 2008.
[abs][pdf]

Ranking Categorical Features Using Generalization Properties: Sivan Sabato, Shai Shalev-Shwartz; 9(Jun):1083--1114, 2008.
[abs][pdf]

A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters: Zach Jorgensen, Yan Zhou, Meador Inge; 9(Jun):1115--1146, 2008.
[abs][pdf]

Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods: Matthias W. Seeger; 9(Jun):1147--1178, 2008.
[abs][pdf]

Consistency of the Group Lasso and Multiple Kernel Learning: Francis R. Bach; 9(Jun):1179--1225, 2008.
[abs][pdf]

Maximal Causes for Non-linear Component Extraction: Jörg Lücke, Maneesh Sahani; 9(Jun):1227--1267, 2008.
[abs][pdf]

Optimal Solutions for Sparse Principal Component Analysis: Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui; 9(Jul):1269--1294, 2008.
[abs][pdf]

Using Markov Blankets for Causal Structure Learning: Jean-Philippe Pellet, André Elisseeff; 9(Jul):1295--1342, 2008.
[abs][pdf]

A Bahadur Representation of the Linear Support Vector Machine: Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim, Changyi Park; 9(Jul):1343--1368, 2008.
[abs][pdf]

Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines: Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin; 9(Jul):1369--1398, 2008.
[abs][pdf]

Online Learning of Complex Prediction Problems Using Simultaneous Projections: Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer; 9(Jul):1399--1435, 2008.
[abs][pdf]

Causal Reasoning with Ancestral Graphs: Jiji Zhang; 9(Jul):1437--1474, 2008.
[abs][pdf]

Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming: Ashwin Srinivasan, Ross D. King; 9(Jul):1475--1533, 2008.
[abs][pdf]

Learning to Combine Motor Primitives Via Greedy Additive Regression: Manu Chhabra, Robert A. Jacobs; 9(Jul):1535--1558, 2008.
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Aggregation of SVM Classifiers Using Sobolev Spaces: Sébastien Loustau; 9(Jul):1559--1582, 2008.
[abs][pdf]

Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction: Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen; 9(Jul):1583--1614, 2008.
[abs][pdf]

Universal Multi-Task Kernels: Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying; 9(Jul):1615--1646, 2008.
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A New Algorithm for Estimating the Effective Dimension-Reduction Subspace: Arnak S. Dalalyan, Anatoly Juditsky, Vladimir Spokoiny; 9(Aug):1647--1678, 2008.
[abs][pdf]

Value Function Based Reinforcement Learning in Changing Markovian Environments: Balázs Csanád Csáji, László Monostori; 9(Aug):1679--1709, 2008.
[abs][pdf]

Regularization on Graphs with Function-adapted Diffusion Processes: Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman; 9(Aug):1711--1739, 2008.
[abs][pdf]

Nearly Uniform Validation Improves Compression-Based Error Bounds: Eric Bax; 9(Aug):1741--1755, 2008.
[abs][pdf]

Learning from Multiple Sources: Koby Crammer, Michael Kearns, Jennifer Wortman; 9(Aug):1757--1774, 2008.
[abs][pdf]

Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks: Michael Collins, Amir Globerson, Terry Koo, Xavier Carreras, Peter L. Bartlett; 9(Aug):1775--1822, 2008.
[abs][pdf]

Classification with a Reject Option using a Hinge Loss: Peter L. Bartlett, Marten H. Wegkamp; 9(Aug):1823--1840, 2008.
[abs][pdf]

Learning Balls of Strings from Edit Corrections: Leonor Becerra-Bonache, Colin de la Higuera, Jean-Christophe Janodet, Frédéric Tantini; 9(Aug):1841--1870, 2008.
[abs][pdf]

LIBLINEAR: A Library for Large Linear Classification (Machine Learning Open Source Software Paper): Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin; 9(Aug):1871--1874, 2008.
[abs][pdf] [code][mloss.org]

On Relevant Dimensions in Kernel Feature Spaces: Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller; 9(Aug):1875--1908, 2008.
[abs][pdf]

Manifold Learning: The Price of Normalization: Yair Goldberg, Alon Zakai, Dan Kushnir, Ya'acov Ritov; 9(Aug):1909--1939, 2008.
[abs][pdf]