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Journal of Machine Learning Research
2006, volume: 7, number:

  1. Janez Demsar
    Statistical Comparisons of Classifiers over Multiple Data Sets. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1-30 [Journal]
  2. Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
    Incremental Algorithms for Hierarchical Classification. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:31-54 [Journal]
  3. Michael Schmitt, Laura Martignon
    On the Complexity of Learning Lexicographic Strategies. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:55-83 [Journal]
  4. Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin
    Generalized Bradley-Terry Models and Multi-Class Probability Estimates. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:85-115 [Journal]
  5. Andreas Maurer
    Bounds for Linear Multi-Task Learning. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:117-139 [Journal]
  6. Masashi Sugiyama
    Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:141-166 [Journal]
  7. Dana Pe'er, Amos Tanay, Aviv Regev
    MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:167-189 [Journal]
  8. Ricardo Silva, Richard Scheines, Clark Glymour, Peter Spirtes
    Learning the Structure of Linear Latent Variable Models. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:191-246 [Journal]
  9. Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny, Klaus-Robert Müller
    In Search of Non-Gaussian Components of a High-Dimensional Distribution. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:247-282 [Journal]
  10. Paul W. Goldberg
    Some Discriminant-Based PAC Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:283-306 [Journal]
  11. Andrea Passerini, Paolo Frasconi, Luc De Raedt
    Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:307-342 [Journal]
  12. Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder, Timothy Sherwood
    Using Machine Learning to Guide Architecture Simulation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:343-378 [Journal]
  13. Ron Begleiter, Ran El-Yaniv
    Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:379-411 [Journal]
  14. Rémi Munos
    Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:413-427 [Journal]
  15. Emanuel Kitzelmann, Ute Schmid
    Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:429-454 [Journal]
  16. Tonatiuh Peña Centeno, Neil D. Lawrence
    Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:455-491 [Journal]
  17. Pat Langley, Dongkyu Choi
    Learning Recursive Control Programs from Problem Solving. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:493-518 [Journal]
  18. Sayan Mukherjee, Ding-Xuan Zhou
    Learning Coordinate Covariances via Gradients. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:519-549 [Journal]
  19. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer
    Online Passive-Aggressive Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:551-585 [Journal]
  20. Adam R. Klivans, Rocco A. Servedio
    Toward Attribute Efficient Learning of Decision Lists and Parities. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:587-602 [Journal]
  21. Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir
    A Direct Method for Building Sparse Kernel Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:603-624 [Journal]
  22. Kazuho Watanabe, Sumio Watanabe
    Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:625-644 [Journal]
  23. Daniil Ryabko
    Pattern Recognition for Conditionally Independent Data. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:645-664 [Journal]
  24. Clayton Scott, Robert D. Nowak
    Learning Minimum Volume Sets. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:665-704 [Journal]
  25. Peter J. Bickel, Yaacov Ritov, Alon Zakai
    Some Theory for Generalized Boosting Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:705-732 [Journal]
  26. Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart
    QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:733-769 [Journal]
  27. Rémi Munos
    Policy Gradient in Continuous Time. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:771-791 [Journal]
  28. Michael W. Spratling
    Learning Image Components for Object Recognition. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:793-815 [Journal]
  29. Régis Vert, Jean-Philippe Vert
    Consistency and Convergence Rates of One-Class SVMs and Related Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:817-854 [Journal]
  30. Ross A. Lippert, Ryan M. Rifkin
    Infinite-sigma Limits For Tikhonov Regularization. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:855-876 [Journal]
  31. Shimon Whiteson, Peter Stone
    Evolutionary Function Approximation for Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:877-917 [Journal]
  32. Sharlee Climer, Weixiong Zhang
    Rearrangement Clustering: Pitfalls, Remedies, and Applications. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:919-943 [Journal]
  33. Seyoung Kim, Padhraic Smyth
    Segmental Hidden Markov Models with Random Effects for Waveform Modeling. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:945-969 [Journal]
  34. Guillaume Lecué
    Lower Bounds and Aggregation in Density Estimation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:971-981 [Journal]
  35. Nicolai Meinshausen
    Quantile Regression Forests. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:983-999 [Journal]
  36. Peter Bühlmann, Bin Yu
    Sparse Boosting. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1001-1024 [Journal]
  37. Andrew B. Gardner, Abba M. Krieger, George J. Vachtsevanos, Brian Litt
    One-Class Novelty Detection for Seizure Analysis from Intracranial EEG. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1025-1044 [Journal]
  38. Alberto Roverato, Milan Studený
    A Graphical Representation of Equivalence Classes of AMP Chain Graphs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1045-1078 [Journal]
  39. Eyal Even-Dar, Shie Mannor, Yishay Mansour
    Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1079-1105 [Journal]
  40. S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola
    Step Size Adaptation in Reproducing Kernel Hilbert Space. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1107-1133 [Journal]
  41. Enrique Castillo, Bertha Guijarro-Berdiñas, Oscar Fontenla-Romero, Amparo Alonso-Betanzos
    A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1159-1182 [Journal]
  42. Jieping Ye, Tao Xiong
    Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1183-1204 [Journal]
  43. Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
    Worst-Case Analysis of Selective Sampling for Linear Classification. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1205-1230 [Journal]
  44. Ichiro Takeuchi, Quoc V. Le, Tim D. Sears, Alexander J. Smola
    Nonparametric Quantile Estimation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1231-1264 [Journal]
  45. Kristin P. Bennett, Emilio Parrado-Hernández
    The Interplay of Optimization and Machine Learning Research. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1265-1281 [Journal]
  46. Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola
    Second Order Cone Programming Approaches for Handling Missing and Uncertain Data. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1283-1314 [Journal]
  47. Yi Zhang, Samuel Burer, W. Nick Street
    Ensemble Pruning Via Semi-definite Programming. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1315-1338 [Journal]
  48. Anders Bergkvist, Peter Damaschke, Marcel Lüthi
    Linear Programs for Hypotheses Selection in Probabilistic Inference Models. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1339-1355 [Journal]
  49. Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao
    Bayesian Network Learning with Parameter Constraints. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1357-1383 [Journal]
  50. Matthias Heiler, Christoph Schnörr
    Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1385-1407 [Journal]
  51. Tijl De Bie, Nello Cristianini
    Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1409-1436 [Journal]
  52. Tobias Glasmachers, Christian Igel
    Maximum-Gain Working Set Selection for SVMs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1437-1466 [Journal]
  53. Luca Zanni, Thomas Serafini, Gaetano Zanghirati
    Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1467-1492 [Journal]
  54. S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste
    Building Support Vector Machines with Reduced Classifier Complexity. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1493-1515 [Journal]
  55. Olvi L. Mangasarian
    Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1517-1530 [Journal]
  56. Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf
    Large Scale Multiple Kernel Learning. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1531-1565 [Journal]
  57. Shai Shalev-Shwartz, Yoram Singer
    Efficient Learning of Label Ranking by Soft Projections onto Polyhedra. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1567-1599 [Journal]
  58. Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
    Kernel-Based Learning of Hierarchical Multilabel Classification Models. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1601-1626 [Journal]
  59. Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan
    Structured Prediction, Dual Extragradient and Bregman Projections. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1627-1653 [Journal]
  60. Hema Raghavan, Omid Madani, Rosie Jones
    Active Learning with Feedback on Features and Instances. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1655-1686 [Journal]
  61. Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou
    Large Scale Transductive SVMs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1687-1712 [Journal]
  62. Francis R. Bach, David Heckerman, Eric Horvitz
    Considering Cost Asymmetry in Learning Classifiers. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1713-1741 [Journal]
  63. Pieter Abbeel, Daphne Koller, Andrew Y. Ng
    Learning Factor Graphs in Polynomial Time and Sample Complexity. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1743-1788 [Journal]
  64. Jelle R. Kok, Nikos A. Vlassis
    Collaborative Multiagent Reinforcement Learning by Payoff Propagation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1789-1828 [Journal]
  65. Martin J. Wainwright
    Estimating the "Wrong" Graphical Model: Benefits in the Computation-Limited Setting. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1829-1859 [Journal]
  66. Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar
    Streamwise Feature Selection. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1861-1885 [Journal]
  67. Chen Yanover, Talya Meltzer, Yair Weiss
    Linear Programming Relaxations and Belief Propagation - An Empirical Study. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1887-1907 [Journal]
  68. Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller
    Incremental Support Vector Learning: Analysis, Implementation and Applications. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1909-1936 [Journal]
  69. Shalabh Bhatnagar, Vivek S. Borkar, Madhukar Akarapu
    A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1937-1962 [Journal]
  70. Francis R. Bach, Michael I. Jordan
    Learning Spectral Clustering, With Application To Speech Separation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1963-2001 [Journal]
  71. Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen, Antti Kerminen
    A Linear Non-Gaussian Acyclic Model for Causal Discovery. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2003-2030 [Journal]
  72. Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky
    Walk-Sums and Belief Propagation in Gaussian Graphical Models. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2031-2064 [Journal]
  73. Thomas Kämpke
    Distance Patterns in Structural Similarity. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2065-2086 [Journal]
  74. Hichem Sahbi, Donald Geman
    A Hierarchy of Support Vector Machines for Pattern Detection. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2087-2123 [Journal]
  75. Fu Chang, Chin-Chin Lin, Chi-Jen Lu
    Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2125-2148 [Journal]
  76. Luis M. de Campos
    A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2149-2187 [Journal]
  77. Tomás Singliar, Milos Hauskrecht
    Noisy-OR Component Analysis and its Application to Link Analysis. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2189-2213 [Journal]
  78. Dana Angluin, Jiang Chen
    Learning a Hidden Hypergraph. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2215-2236 [Journal]
  79. Katya Scheinberg
    An Efficient Implementation of an Active Set Method for SVMs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2237-2257 [Journal]
  80. Anders Jonsson, Andrew G. Barto
    Causal Graph Based Decomposition of Factored MDPs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2259-2301 [Journal]
  81. Mikio L. Braun
    Accurate Error Bounds for the Eigenvalues of the Kernel Matrix. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2303-2328 [Journal]
  82. Josep M. Porta, Nikos A. Vlassis, Matthijs T. J. Spaan, Pascal Poupart
    Point-Based Value Iteration for Continuous POMDPs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2329-2367 [Journal]
  83. David A. Ross, Richard S. Zemel
    Learning Parts-Based Representations of Data. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2369-2397 [Journal]
  84. Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
    Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2399-2434 [Journal]
  85. Di-Rong Chen, Tao Sun
    Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2435-2447 [Journal]
  86. Magnus Ekdahl, Timo Koski
    Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2449-2480 [Journal]
  87. Sayan Mukherjee, Qiang Wu
    Estimation of Gradients and Coordinate Covariation in Classification. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2481-2514 [Journal]
  88. David Barber
    Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2515-2540 [Journal]
  89. Peng Zhao, Bin Yu
    On Model Selection Consistency of Lasso. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:2541-2563 [Journal]
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