JMLR Volume 7

• Statistical Comparisons of Classifiers over Multiple Data Sets

  Janez Demšar (1):1−30, 2006 PDF BibTeX

• Incremental Algorithms for Hierarchical Classification

  Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni (2):31−54, 2006 PDF BibTeX

• On the Complexity of Learning Lexicographic Strategies

  Michael Schmitt, Laura Martignon (3):55−83, 2006 PDF BibTeX

• Generalized Bradley-Terry Models and Multi-Class Probability Estimates

  Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin (4):85−115, 2006 PDF BibTeX

• Bounds for Linear Multi-Task Learning

  Andreas Maurer (5):117−139, 2006 PDF BibTeX

• Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error

  Masashi Sugiyama (6):141−166, 2006 PDF BibTeX

• MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals

  Dana Pe'er, Amos Tanay, Aviv Regev (7):167−189, 2006 PDF BibTeX

• Learning the Structure of Linear Latent Variable Models

  Ricardo Silva, Richard Scheine, Clark Glymour, Peter Spirtes (8):191−246, 2006 PDF BibTeX

• In Search of Non-Gaussian Components of a High-Dimensional Distribution

  Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny, Klaus-Robert Müller (9):247−282, 2006 PDF BibTeX

• Some Discriminant-Based PAC Algorithms

  Paul W. Goldberg (10):283−306, 2006 PDF BibTeX

• Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting

  Andrea Passerini, Paolo Frasconi, Luc De Raedt (11):307−342, 2006 PDF BibTeX

• Using Machine Learning to Guide Architecture Simulation

  Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder, Timothy Sherwood (12):343−378, 2006 PDF BibTeX

• Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition

  Ron Begleiter, Ran El-Yaniv (13):379−411, 2006 PDF BibTeX

• Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation

  Rémi Munos (14):413−427, 2006 PDF BibTeX

• Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach

  Emanuel Kitzelmann, Ute Schmid (15):429−454, 2006 PDF BibTeX

• Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis

  Tonatiuh Peña Centeno, Neil D. Lawrence (16):455−491, 2006 PDF BibTeX

• Learning Recursive Control Programs from Problem Solving

  Pat Langley, Dongkyu Choi (17):493−518, 2006 PDF BibTeX

• Learning Coordinate Covariances via Gradients

  Sayan Mukherjee, Ding-Xuan Zhou (18):519−549, 2006 PDF BibTeX

• Online Passive-Aggressive Algorithms

  Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer (19):551−585, 2006 PDF BibTeX

• Toward Attribute Efficient Learning of Decision Lists and Parities

  Adam R. Klivans, Rocco A. Servedio (20):587−602, 2006 PDF BibTeX

• A Direct Method for Building Sparse Kernel Learning Algorithms

  Mingrui Wu, Bernhard Schölkopf, Gökhan Bakir (21):603−624, 2006 PDF BibTeX

• Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation

  Kazuho Watanabe, Sumio Watanabe (22):625−644, 2006 PDF BibTeX

• Pattern Recognition for Conditionally Independent Data

  Daniil Ryabko (23):645−664, 2006 PDF BibTeX

• Learning Minimum Volume Sets

  Clayton D. Scott, Robert D. Nowak (24):665−704, 2006 PDF BibTeX

• Some Theory for Generalized Boosting Algorithms

  Peter J. Bickel, Ya'acov Ritov, Alon Zakai (25):705−732, 2006 PDF BibTeX

• QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines

  Don Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart (26):733−769, 2006 PDF BibTeX

• Policy Gradient in Continuous Time

  Rémi Munos (27):771−791, 2006 PDF BibTeX

• Learning Image Components for Object Recognition

  Michael W. Spratling (28):793−815, 2006 PDF BibTeX

• Consistency and Convergence Rates of One-Class SVMs and Related Algorithms

  Régis Vert, Jean-Philippe Vert (29):817−854, 2006 PDF BibTeX

• Infinite-σ Limits For Tikhonov Regularization

  Ross A. Lippert, Ryan M. Rifkin (30):855−876, 2006 PDF BibTeX

• Evolutionary Function Approximation for Reinforcement Learning

  Shimon Whiteson, Peter Stone (31):877−917, 2006 PDF BibTeX

• Rearrangement Clustering: Pitfalls, Remedies, and Applications

  Sharlee Climer, Weixiong Zhang (32):919−943, 2006 PDF BibTeX

• Segmental Hidden Markov Models with Random Effects for Waveform Modeling

  Seyoung Kim, Padhraic Smyth (33):945−969, 2006 PDF BibTeX

• Lower Bounds and Aggregation in Density Estimation

  Guillaume Lecué (34):971−981, 2006 PDF BibTeX

• Quantile Regression Forests

  Nicolai Meinshausen (35):983−999, 2006 PDF BibTeX

• Sparse Boosting

  Peter Bühlmann, Bin Yu (36):1001−1024, 2006 PDF BibTeX

• One-Class Novelty Detection for Seizure Analysis from Intracranial EEG

  Andrew B. Gardner, Abba M. Krieger, George Vachtsevanos, Brian Litt (37):1025−1044, 2006 PDF BibTeX

• A Graphical Representation of Equivalence Classes of AMP Chain Graphs

  Alberto Roverato, Milan Studený (38):1045−1078, 2006 PDF BibTeX

• Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems

  Eyal Even-Dar, Shie Mannor, Yishay Mansour (39):1079−1105, 2006 PDF BibTeX

• Step Size Adaptation in Reproducing Kernel Hilbert Space

  S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola (40):1107−1133, 2006 PDF BibTeX

• New Algorithms for Efficient High-Dimensional Nonparametric Classification

  Ting Liu, Andrew W. Moore, Alexander Gray (41):1135−1158, 2006 PDF BibTeX

• A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis

  Enrique Castillo, Bertha Guijarro-Berdiñas, Oscar Fontenla-Romero, Amparo Alonso-Betanzos (42):1159−1182, 2006 PDF BibTeX

• Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis

  Jieping Ye, Tao Xiong (43):1183−1204, 2006 PDF BibTeX

• Worst-Case Analysis of Selective Sampling for Linear Classification

  Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni (44):1205−1230, 2006 PDF BibTeX

• Nonparametric Quantile Estimation

  Ichiro Takeuchi, Quoc V. Le, Timothy D. Sears, Alexander J. Smola (45):1231−1264, 2006 PDF BibTeX

• The Interplay of Optimization and Machine Learning Research

  Kristin P. Bennett, Emilio Parrado-Hernández (46):1265−1281, 2006 PDF BibTeX

• Second Order Cone Programming Approaches for Handling Missing and Uncertain Data

  Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola (47):1283−1314, 2006 PDF BibTeX

• Ensemble Pruning Via Semi-definite Programming

  Yi Zhang, Samuel Burer, W. Nick Street (48):1315−1338, 2006 PDF BibTeX

• Linear Programs for Hypotheses Selection in Probabilistic Inference Models

  Anders Bergkvist, Peter Damaschke, Marcel Lüthi (49):1339−1355, 2006 PDF BibTeX

• Bayesian Network Learning with Parameter Constraints

  Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao (50):1357−1383, 2006 PDF BibTeX

• Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming

  Matthias Heiler, Christoph Schnörr (51):1385−1407, 2006 PDF BibTeX

• Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems

  Tijl De Bie, Nello Cristianini (52):1409−1436, 2006 PDF BibTeX

• Maximum-Gain Working Set Selection for SVMs

  Tobias Glasmachers, Christian Igel (53):1437−1466, 2006 PDF BibTeX

• Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems

  Luca Zanni, Thomas Serafini, Gaetano Zanghirati (54):1467−1492, 2006 PDF BibTeX

• Building Support Vector Machines with Reduced Classifier Complexity

  S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste (55):1493−1515, 2006 PDF BibTeX

• Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization

  Olvi L. Mangasarian (56):1517−1530, 2006 PDF BibTeX

• Large Scale Multiple Kernel Learning

  Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf (57):1531−1565, 2006 PDF BibTeX

• Efficient Learning of Label Ranking by Soft Projections onto Polyhedra

  Shai Shalev-Shwartz, Yoram Singer (58):1567−1599, 2006 PDF BibTeX

• Kernel-Based Learning of Hierarchical Multilabel Classification Models

  Juho Rousu, Craig Saunders, Sandor Szedmak, John Shawe-Taylor (59):1601−1626, 2006 PDF BibTeX

• Structured Prediction, Dual Extragradient and Bregman Projections

  Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan (60):1627−1653, 2006 PDF BibTeX

• Active Learning with Feedback on Features and Instances

  Hema Raghavan, Omid Madani, Rosie Jones (61):1655−1686, 2006 PDF BibTeX

• Large Scale Transductive SVMs

  Ronan Collobert, Fabian Sinz, Jason Weston, Léon Bottou (62):1687−1712, 2006 PDF BibTeX

• Considering Cost Asymmetry in Learning Classifiers

  Francis R. Bach, David Heckerman, Eric Horvitz (63):1713−1741, 2006 PDF BibTeX

• Learning Factor Graphs in Polynomial Time and Sample Complexity

  Pieter Abbeel, Daphne Koller, Andrew Y. Ng (64):1743−1788, 2006 PDF BibTeX

• Collaborative Multiagent Reinforcement Learning by Payoff Propagation

  Jelle R. Kok, Nikos Vlassis (65):1789−1828, 2006 PDF BibTeX

• Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting

  Martin J. Wainwright (66):1829−1859, 2006 PDF BibTeX

• Streamwise Feature Selection

  Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar (67):1861−1885, 2006 PDF BibTeX

• Linear Programming Relaxations and Belief Propagation -- An Empirical Study

  Chen Yanover, Talya Meltzer, Yair Weiss (68):1887−1907, 2006 PDF BibTeX

• Incremental Support Vector Learning: Analysis, Implementation and Applications

  Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller (69):1909−1936, 2006 PDF BibTeX

• A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events

  Shalabh Bhatnagar, Vivek S. Borkar, Madhukar Akarapu (70):1937−1962, 2006 PDF BibTeX

• Learning Spectral Clustering, With Application To Speech Separation

  Francis R. Bach, Michael I. Jordan (71):1963−2001, 2006 PDF BibTeX

• A Linear Non-Gaussian Acyclic Model for Causal Discovery

  Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen, Antti Kerminen (72):2003−2030, 2006 PDF BibTeX

• Walk-Sums and Belief Propagation in Gaussian Graphical Models

  Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky (73):2031−2064, 2006 PDF BibTeX

• Distance Patterns in Structural Similarity

  Thomas Kämpke (74):2065−2086, 2006 PDF BibTeX

• A Hierarchy of Support Vector Machines for Pattern Detection

  Hichem Sahbi, Donald Geman (75):2087−2123, 2006 PDF BibTeX

• Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies

  Fu Chang, Chin-Chin Lin, Chi-Jen Lu (76):2125−2148, 2006 PDF BibTeX

• A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests

  Luis M. de Campos (77):2149−2187, 2006 PDF BibTeX

• Noisy-OR Component Analysis and its Application to Link Analysis

  Tomáš Šingliar, Miloš Hauskrecht (78):2189−2213, 2006 PDF BibTeX

• Learning a Hidden Hypergraph

  Dana Angluin, Jiang Chen (79):2215−2236, 2006 PDF BibTeX

• An Efficient Implementation of an Active Set Method for SVMs

  Katya Scheinberg (80):2237−2257, 2006 PDF BibTeX

• Causal Graph Based Decomposition of Factored MDPs

  Anders Jonsson, Andrew Barto (81):2259−2301, 2006 PDF BibTeX

• Accurate Error Bounds for the Eigenvalues of the Kernel Matrix

  Mikio L. Braun (82):2303−2328, 2006 PDF BibTeX

• Point-Based Value Iteration for Continuous POMDPs

  Josep M. Porta, Nikos Vlassis, Matthijs T.J. Spaan, Pascal Poupart (83):2329−2367, 2006 PDF BibTeX

• Learning Parts-Based Representations of Data

  David A. Ross, Richard S. Zemel (84):2369−2397, 2006 PDF BibTeX

• Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

  Mikhail Belkin, Partha Niyogi, Vikas Sindhwani (85):2399−2434, 2006 PDF BibTeX

• Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss

  Di-Rong Chen, Tao Sun (86):2435−2447, 2006 PDF BibTeX

• Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation

  Magnus Ekdahl, Timo Koski (87):2449−2480, 2006 PDF BibTeX

• Estimation of Gradients and Coordinate Covariation in Classification

  Sayan Mukherjee, Qiang Wu (88):2481−2514, 2006 PDF BibTeX

• Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems

  David Barber (89):2515−2540, 2006 PDF BibTeX

• On Model Selection Consistency of Lasso

  Peng Zhao, Bin Yu (90):2541−2563, 2006 PDF BibTeX

• Stability Properties of Empirical Risk Minimization over Donsker Classes

  Andrea Caponnetto, Alexander Rakhlin (91):2565−2583, 2006 PDF BibTeX

• Linear State-Space Models for Blind Source Separation

  Rasmus Kongsgaard Olsson, Lars Kai Hansen (92):2585−2602, 2006 PDF BibTeX

• On Representing and Generating Kernels by Fuzzy Equivalence Relations

  Bernhard Moser (93):2603−2620, 2006 PDF BibTeX

• A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n

  Robert Castelo, Alberto Roverato (94):2621−2650, 2006 PDF BibTeX

• Universal Kernels

  Charles A. Micchelli, Yuesheng Xu, Haizhang Zhang (95):2651−2667, 2006 PDF BibTeX

• Machine Learning for Computer Security

  Philip K. Chan, Richard P. Lippmann (96):2669−2672, 2006 PDF BibTeX

• Spam Filtering Using Statistical Data Compression Models

  Andrej Bratko, Gordon V. Cormack, Bogdan Filipič, Thomas R. Lynam, Blaž Zupan (97):2673−2698, 2006 PDF BibTeX

• Spam Filtering Based On The Analysis Of Text Information Embedded Into Images

  Giorgio Fumera, Ignazio Pillai, Fabio Roli (98):2699−2720, 2006 PDF BibTeX

• Learning to Detect and Classify Malicious Executables in the Wild

  J. Zico Kolter, Marcus A. Maloof (99):2721−2744, 2006 PDF BibTeX

• On Inferring Application Protocol Behaviors in Encrypted Network Traffic

  Charles V. Wright, Fabian Monrose, Gerald M. Masson (100):2745−2769, 2006 PDF BibTeX