JMLR Volume 8

• Nonlinear Boosting Projections for Ensemble Construction

  Nicolás García-Pedrajas, César García-Osorio, Colin Fyfe (1):1−33, 2007 PDF BibTeX

• Multi-Task Learning for Classification with Dirichlet Process Priors

  Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram (2):35−63, 2007 PDF BibTeX

• A Unified Continuous Optimization Framework for Center-Based Clustering Methods

  Marc Teboulle (3):65−102, 2007 PDF BibTeX

• Minimax Regret Classifier for Imprecise Class Distributions

  Rocío Alaiz-Rodríguez, Alicia Guerrero-Curieses, Jesús Cid-Sueiro (4):103−130, 2007 PDF BibTeX

• Distances between Data Sets Based on Summary Statistics

  Nikolaj Tatti (5):131−154, 2007 PDF BibTeX

• Building Blocks for Variational Bayesian Learning of Latent Variable Models

  Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen (6):155−201, 2007 PDF BibTeX

• A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians

  Sanjoy Dasgupta, Leonard Schulman (7):203−226, 2007 PDF BibTeX

• Noise Tolerant Variants of the Perceptron Algorithm

  Roni Khardon, Gabriel Wachman (8):227−248, 2007 PDF BibTeX

• Learnability of Gaussians with Flexible Variances

  Yiming Ying, Ding-Xuan Zhou (9):249−276, 2007 PDF BibTeX

• Separating Models of Learning from Correlated and Uncorrelated Data

  Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andrew Wan (10):277−290, 2007 PDF BibTeX

• Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets"

  Gaëlle Loosli, Stéphane Canu (11):291−301, 2007 PDF BibTeX

• General Polynomial Time Decomposition Algorithms

  Nikolas List, Hans Ulrich Simon (12):303−321, 2007 PDF BibTeX

• Dynamics and Generalization Ability of LVQ Algorithms

  Michael Biehl, Anarta Ghosh, Barbara Hammer (13):323−360, 2007 PDF BibTeX

• Statistical Consistency of Kernel Canonical Correlation Analysis

  Kenji Fukumizu, Francis R. Bach, Arthur Gretton (14):361−383, 2007 PDF BibTeX

• Learning Equivariant Functions with Matrix Valued Kernels

  Marco Reisert, Hans Burkhardt (15):385−408, 2007 PDF BibTeX

• Boosted Classification Trees and Class Probability/Quantile Estimation

  David Mease, Abraham J. Wyner, Andreas Buja (16):409−439, 2007 PDF BibTeX

• Value Regularization and Fenchel Duality

  Ryan M. Rifkin, Ross A. Lippert (17):441−479, 2007 PDF BibTeX

• Integrating Naïve Bayes and FOIL

  Niels Landwehr, Kristian Kersting, Luc De Raedt (18):481−507, 2007 PDF BibTeX

• A Stochastic Algorithm for Feature Selection in Pattern Recognition

  Sébastien Gadat, Laurent Younes (19):509−547, 2007 PDF BibTeX

• Learning Horn Expressions with LOGAN-H

  Marta Arias, Roni Khardon, Jérôme Maloberti (20):549−587, 2007 PDF BibTeX

• Consistent Feature Selection for Pattern Recognition in Polynomial Time

  Roland Nilsson, José M. Peña, Johan Björkegren, Jesper Tegnér (21):589−612, 2007 PDF BibTeX

• Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm

  Markus Kalisch, Peter Bühlmann (22):613−636, 2007 PDF BibTeX

• Margin Trees for High-dimensional Classification

  Robert Tibshirani, Trevor Hastie (23):637−652, 2007 PDF BibTeX

• Relational Dependency Networks

  Jennifer Neville, David Jensen (24):653−692, 2007 PDF BibTeX

• Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data

  Charles Sutton, Andrew McCallum, Khashayar Rohanimanesh (25):693−723, 2007 PDF BibTeX

• The Pyramid Match Kernel: Efficient Learning with Sets of Features

  Kristen Grauman, Trevor Darrell (26):725−760, 2007 PDF BibTeX

• Infinitely Imbalanced Logistic Regression

  Art B. Owen (27):761−773, 2007 PDF BibTeX

• Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results

  Peter L. Bartlett, Ambuj Tewari (28):775−790, 2007 PDF BibTeX

• Concave Learners for Rankboost

  Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang (29):791−812, 2007 PDF BibTeX

• Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression

  Shantanu Chakrabartty, Gert Cauwenberghs (30):813−839, 2007 PDF BibTeX

• Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters

  Gavin C. Cawley, Nicola L. C. Talbot (31):841−861, 2007 PDF BibTeX

• Combining PAC-Bayesian and Generic Chaining Bounds

  Jean-Yves Audibert, Olivier Bousquet (32):863−889, 2007 PDF BibTeX

• Anytime Learning of Decision Trees

  Saher Esmeir, Shaul Markovitch (33):891−933, 2007 PDF BibTeX

• Classification in Networked Data: A Toolkit and a Univariate Case Study

  Sofus A. Macskassy, Foster Provost (34):935−983, 2007 PDF BibTeX

• Covariate Shift Adaptation by Importance Weighted Cross Validation

  Masashi Sugiyama, Matthias Krauledat, Klaus-Robert Müller (35):985−1005, 2007 PDF BibTeX

• On the Consistency of Multiclass Classification Methods

  Ambuj Tewari, Peter L. Bartlett (36):1007−1025, 2007 PDF BibTeX

• Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis

  Masashi Sugiyama (37):1027−1061, 2007 PDF BibTeX

• Undercomplete Blind Subspace Deconvolution

  Zoltán Szabó, Barnabás Póczos, András Lőrincz (38):1063−1095, 2007 PDF BibTeX

• Bilinear Discriminant Component Analysis

  Mads Dyrholm, Christoforos Christoforou, Lucas C. Parra (39):1097−1111, 2007 PDF BibTeX

• Loop Corrections for Approximate Inference on Factor Graphs

  Joris M. Mooij, Hilbert J. Kappen (40):1113−1143, 2007 PDF BibTeX

• Penalized Model-Based Clustering with Application to Variable Selection

  Wei Pan, Xiaotong Shen (41):1145−1164, 2007 PDF BibTeX

• Local Discriminant Wavelet Packet Coordinates for Face Recognition

  Chao-Chun Liu, Dao-Qing Dai, Hong Yan (42):1165−1195, 2007 PDF BibTeX

• Synergistic Face Detection and Pose Estimation with Energy-Based Models

  Margarita Osadchy, Yann Le Cun, Matthew L. Miller (43):1197−1215, 2007 PDF BibTeX

• Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling

  Miroslav Dudík, Steven J. Phillips, Robert E. Schapire (44):1217−1260, 2007 PDF BibTeX

• Measuring Differentiability: Unmasking Pseudonymous Authors

  Moshe Koppel, Jonathan Schler, Elisheva Bonchek-Dokow (45):1261−1276, 2007 PDF BibTeX

• Bayesian Quadratic Discriminant Analysis

  Santosh Srivastava, Maya R. Gupta, Béla A. Frigyik (46):1277−1305, 2007 PDF BibTeX

• From External to Internal Regret

  Avrim Blum, Yishay Mansour (47):1307−1324, 2007 PDF BibTeX

• Graph Laplacians and their Convergence on Random Neighborhood Graphs

  Matthias Hein, Jean-Yves Audibert, Ulrike von Luxburg (48):1325−1368, 2007 PDF BibTeX

• Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption

  Philippe Rigollet (49):1369−1392, 2007 PDF BibTeX

• Learning to Classify Ordinal Data: The Data Replication Method

  Jaime S. Cardoso, Joaquim F. Pinto da Costa (50):1393−1429, 2007 PDF BibTeX

• Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions

  Vitaly Feldman (51):1431−1460, 2007 PDF BibTeX

• PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers

  François Laviolette, Mario Marchand (52):1461−1487, 2007 PDF BibTeX

• On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning

  Rie Johnson, Tong Zhang (53):1489−1517, 2007 PDF BibTeX

• An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression

  Kwangmoo Koh, Seung-Jean Kim, Stephen Boyd (54):1519−1555, 2007 PDF BibTeX

• Multi-class Protein Classification Using Adaptive Codes

  Iain Melvin, Eugene Ie, Jason Weston, William Stafford Noble, Christina Leslie (55):1557−1581, 2007 PDF BibTeX

• Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification

  Onur C. Hamsici, Aleix M. Martinez (56):1583−1623, 2007 PDF BibTeX

• Handling Missing Values when Applying Classification Models

  Maytal Saar-Tsechansky, Foster Provost (57):1623−1657, 2007 PDF BibTeX

• Compression-Based Averaging of Selective Naive Bayes Classifiers

  Marc Boullé (58):1659−1685, 2007 PDF BibTeX

• A Nonparametric Statistical Approach to Clustering via Mode Identification

  Jia Li, Surajit Ray, Bruce G. Lindsay (59):1687−1723, 2007 PDF BibTeX

• Polynomial Identification in the Limit of Substitutable Context-free Languages

  Alexander Clark, Rémi Eyraud (60):1725−1745, 2007 PDF BibTeX

• Structure and Majority Classes in Decision Tree Learning

  Ray J. Hickey (61):1747−1768, 2007 PDF BibTeX

• Characterizing the Function Space for Bayesian Kernel Models

  Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert (62):1769−1797, 2007 PDF BibTeX

• "Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks

  Gal Elidan, Iftach Nachman, Nir Friedman (63):1799−1833, 2007 PDF BibTeX

• Behavioral Shaping for Geometric Concepts

  Manu Chhabra, Robert A. Jacobs, Daniel Štefankovič (64):1835−1865, 2007 PDF BibTeX

• Large Margin Semi-supervised Learning

  Junhui Wang, Xiaotong Shen (65):1867−1891, 2007 PDF BibTeX

• Fast Iterative Kernel Principal Component Analysis

  Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan (66):1893−1918, 2007 PDF BibTeX

• A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation

  Arindam Banerjee, Inderjit Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha (67):1919−1986, 2007 PDF BibTeX

• Truncating the Loop Series Expansion for Belief Propagation

  Vicenç Gómez, Joris M. Mooij, Hilbert J. Kappen (68):1987−2016, 2007 PDF BibTeX

• Very Fast Online Learning of Highly Non Linear Problems

  Aggelos Chariatis (69):2017−2045, 2007 PDF BibTeX

• Unlabeled Compression Schemes for Maximum Classes

  Dima Kuzmin, Manfred K. Warmuth (70):2047−2081, 2007 PDF BibTeX

• Refinable Kernels

  Yuesheng Xu, Haizhang Zhang (71):2083−2120, 2007 PDF BibTeX

• A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion

  Marco Loog (72):2121−2123, 2007 PDF BibTeX

• Transfer Learning via Inter-Task Mappings for Temporal Difference Learning

  Matthew E. Taylor, Peter Stone, Yaxin Liu (73):2125−2167, 2007 PDF BibTeX

• Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes

  Sridhar Mahadevan, Mauro Maggioni (74):2169−2231, 2007 PDF BibTeX

• Online Learning of Multiple Tasks with a Shared Loss

  Ofer Dekel, Philip M. Long, Yoram Singer (75):2233−2264, 2007 PDF BibTeX

• Euclidean Embedding of Co-occurrence Data

  Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby (76):2265−2295, 2007 PDF BibTeX

• Harnessing the Expertise of 70,000 Human Editors: Knowledge-Based Feature Generation for Text Categorization

  Evgeniy Gabrilovich, Shaul Markovitch (77):2297−2345, 2007 PDF BibTeX

• AdaBoost is Consistent

  Peter L. Bartlett, Mikhail Traskin (78):2347−2368, 2007 PDF BibTeX

• The On-Line Shortest Path Problem Under Partial Monitoring

  András György, Tamás Linder, Gábor Lugosi, György Ottucsák (79):2369−2403, 2007 PDF BibTeX

• The Locally Weighted Bag of Words Framework for Document Representation

  Guy Lebanon, Yi Mao, Joshua Dillon (80):2405−2441, 2007 PDF BibTeX

• The Need for Open Source Software in Machine Learning

  Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson (81):2443−2466, 2007 PDF BibTeX

• On the Representer Theorem and Equivalent Degrees of Freedom of SVR

  Francesco Dinuzzo, Marta Neve, Giuseppe De Nicolao, Ugo Pietro Gianazza (82):2467−2495, 2007 PDF BibTeX

• Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections

  Ping Li, Trevor J. Hastie, Kenneth W. Church (83):2497−2532, 2007 PDF BibTeX

• Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data

  Zakria Hussain, François Laviolette, Mario Marchand, John Shawe-Taylor, Spencer Charles Brubaker, Matthew D. Mullin (84):2533−2549, 2007 PDF BibTeX

• VC Theory of Large Margin Multi-Category Classifiers

  Yann Guermeur (85):2551−2594, 2007 PDF BibTeX

• Learning in Environments with Unknown Dynamics: Towards more Robust Concept Learners

  Marlon Núñez, Raúl Fidalgo, Rafael Morales (86):2595−2628, 2007 PDF BibTeX

• Hierarchical Average Reward Reinforcement Learning

  Mohammad Ghavamzadeh, Sridhar Mahadevan (87):2629−2669, 2007 PDF BibTeX

• Ranking the Best Instances

  Stéphan Clémençon, Nicolas Vayatis (88):2671−2699, 2007 PDF BibTeX

• Stagewise Lasso

  Peng Zhao, Bin Yu (89):2701−2726, 2007 PDF BibTeX

• A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning

  Carine Hue, Marc Boullé (90):2727−2754, 2007 PDF BibTeX

• Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts

  J. Zico Kolter, Marcus A. Maloof (91):2755−2790, 2007 PDF BibTeX