JMLR Volume 8

Nonlinear Boosting Projections for Ensemble Construction
Nicolás García-Pedrajas, César García-Osorio, Colin Fyfe; 8(Jan):1--33, 2007.
[abs][pdf]

Multi-Task Learning for Classification with Dirichlet Process Priors
Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram; 8(Jan):35--63, 2007.
[abs][pdf]

A Unified Continuous Optimization Framework for Center-Based Clustering Methods
Marc Teboulle; 8(Jan):65--102, 2007.
[abs][pdf]

Minimax Regret Classifier for Imprecise Class Distributions
Rocío Alaiz-Rodríguez, Alicia Guerrero-Curieses, Jesús Cid-Sueiro; 8(Jan):103--130, 2007.
[abs][pdf]

Distances between Data Sets Based on Summary Statistics
Nikolaj Tatti; 8(Jan):131--154, 2007.
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Building Blocks for Variational Bayesian Learning of Latent Variable Models
Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen; 8(Jan):155--201, 2007.
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A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians
Sanjoy Dasgupta, Leonard Schulman; 8(Feb):203--226, 2007.
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Noise Tolerant Variants of the Perceptron Algorithm
Roni Khardon, Gabriel Wachman; 8(Feb):227--248, 2007.
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Learnability of Gaussians with Flexible Variances
Yiming Ying, Ding-Xuan Zhou; 8(Feb):249--276, 2007.
[abs][pdf]

Separating Models of Learning from Correlated and Uncorrelated Data     (Special Topic on the Conference on Learning Theory 2005)
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andrew Wan; 8(Feb):277--290, 2007.
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Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"
Gaëlle Loosli, Stéphane Canu; 8(Feb):291--301, 2007.
[abs][pdf]

General Polynomial Time Decomposition Algorithms     (Special Topic on the Conference on Learning Theory 2005)
Nikolas List, Hans Ulrich Simon; 8(Feb):303--321, 2007.
[abs][pdf]

Dynamics and Generalization Ability of LVQ Algorithms
Michael Biehl, Anarta Ghosh, Barbara Hammer; 8(Feb):323--360, 2007.
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Statistical Consistency of Kernel Canonical Correlation Analysis
Kenji Fukumizu, Francis R. Bach, Arthur Gretton; 8(Feb):361--383, 2007.
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Learning Equivariant Functions with Matrix Valued Kernels
Marco Reisert, Hans Burkhardt; 8(Mar):385--408, 2007.
[abs][pdf]

Boosted Classification Trees and Class Probability/Quantile Estimation
David Mease, Abraham J. Wyner, Andreas Buja; 8(Mar):409--439, 2007.
[abs][pdf]

Value Regularization and Fenchel Duality
Ryan M. Rifkin, Ross A. Lippert; 8(Mar):441--479, 2007.
[abs][pdf]

Integrating Naïve Bayes and FOIL
Niels Landwehr, Kristian Kersting, Luc De Raedt; 8(Mar):481--507, 2007.
[abs][pdf]

A Stochastic Algorithm for Feature Selection in Pattern Recognition
Sébastien Gadat, Laurent Younes; 8(Mar):509--547, 2007.
[abs][pdf]

Learning Horn Expressions with LOGAN-H
Marta Arias, Roni Khardon, Jérôme Maloberti; 8(Mar):549--587, 2007.
[abs][pdf]

Consistent Feature Selection for Pattern Recognition in Polynomial Time
Roland Nilsson, José M. Peña, Johan Björkegren, Jesper Tegnér; 8(Mar):589--612, 2007.
[abs][pdf]

Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm
Markus Kalisch, Peter Bühlmann; 8(Mar):613--636, 2007.
[abs][pdf]

Margin Trees for High-dimensional Classification
Robert Tibshirani, Trevor Hastie; 8(Mar):637--652, 2007.
[abs][pdf]

Relational Dependency Networks
Jennifer Neville, David Jensen; 8(Mar):653--692, 2007.
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Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data
Charles Sutton, Andrew McCallum, Khashayar Rohanimanesh; 8(Mar):693--723, 2007.
[abs][pdf]

The Pyramid Match Kernel: Efficient Learning with Sets of Features
Kristen Grauman, Trevor Darrell; 8(Apr):725--760, 2007.
[abs][pdf]

Infinitely Imbalanced Logistic Regression
Art B. Owen; 8(Apr):761--773, 2007.
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Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results
Peter L. Bartlett, Ambuj Tewari; 8(Apr):775--790, 2007.
[abs][pdf]

Concave Learners for Rankboost
Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang; 8(Apr):791--812, 2007.
[abs][pdf]

Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression
Shantanu Chakrabartty, Gert Cauwenberghs; 8(Apr):813--839, 2007.
[abs][pdf]

Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters     (Special Topic on Model Selection)
Gavin C. Cawley, Nicola L. C. Talbot; 8(Apr):841--861, 2007.
[abs][pdf]

Combining PAC-Bayesian and Generic Chaining Bounds
Jean-Yves Audibert, Olivier Bousquet; 8(Apr):863--889, 2007.
[abs][pdf]

Anytime Learning of Decision Trees
Saher Esmeir, Shaul Markovitch; 8(May):891--933, 2007.
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Classification in Networked Data: A Toolkit and a Univariate Case Study
Sofus A. Macskassy, Foster Provost; 8(May):935--983, 2007.
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Covariate Shift Adaptation by Importance Weighted Cross Validation
Masashi Sugiyama, Matthias Krauledat, Klaus-Robert Müller; 8(May):985--1005, 2007.
[abs][pdf]

On the Consistency of Multiclass Classification Methods     (Special Topic on the Conference on Learning Theory 2005)
Ambuj Tewari, Peter L. Bartlett; 8(May):1007--1025, 2007.
[abs][pdf]

Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
Masashi Sugiyama; 8(May):1027--1061, 2007.
[abs][pdf]

Undercomplete Blind Subspace Deconvolution
Zoltán Szabó, Barnabás Póczos, András Lőrincz; 8(May):1063--1095, 2007.
[abs][pdf]

Bilinear Discriminant Component Analysis
Mads Dyrholm, Christoforos Christoforou, Lucas C. Parra; 8(May):1097--1111, 2007.
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Loop Corrections for Approximate Inference on Factor Graphs
Joris M. Mooij, Hilbert J. Kappen; 8(May):1113--1143, 2007.
[abs][pdf]

Penalized Model-Based Clustering with Application to Variable Selection
Wei Pan, Xiaotong Shen; 8(May):1145--1164, 2007.
[abs][pdf]

Local Discriminant Wavelet Packet Coordinates for Face Recognition
Chao-Chun Liu, Dao-Qing Dai, Hong Yan; 8(May):1165--1195, 2007.
[abs][pdf]

Synergistic Face Detection and Pose Estimation with Energy-Based Models
Margarita Osadchy, Yann Le Cun, Matthew L. Miller; 8(May):1197--1215, 2007.
[abs][pdf]

Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling
Miroslav Dudík, Steven J. Phillips, Robert E. Schapire; 8(Jun):1217--1260, 2007.
[abs][pdf]

Measuring Differentiability: Unmasking Pseudonymous Authors
Moshe Koppel, Jonathan Schler, Elisheva Bonchek-Dokow; 8(Jun):1261--1276, 2007.
[abs][pdf]

Bayesian Quadratic Discriminant Analysis
Santosh Srivastava, Maya R. Gupta, Béla A. Frigyik; 8(Jun):1277--1305, 2007.
[abs][pdf]

From External to Internal Regret     (Special Topic on the Conference on Learning Theory 2005)
Avrim Blum, Yishay Mansour; 8(Jun):1307--1324, 2007.
[abs][pdf]

Graph Laplacians and their Convergence on Random Neighborhood Graphs     (Special Topic on the Conference on Learning Theory 2005)
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxburg; 8(Jun):1325--1368, 2007.
[abs][pdf]

Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
Philippe Rigollet; 8(Jul):1369--1392, 2007.
[abs][pdf]

Learning to Classify Ordinal Data: The Data Replication Method
Jaime S. Cardoso, Joaquim F. Pinto da Costa; 8(Jul):1393--1429, 2007.
[abs][pdf]

Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions     (Special Topic on the Conference on Learning Theory 2005)
Vitaly Feldman; 8(Jul):1431--1460, 2007.
[abs][pdf]

PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers
François Laviolette, Mario Marchand; 8(Jul):1461--1487, 2007.
[abs][pdf]

On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning
Rie Johnson, Tong Zhang; 8(Jul):1489--1517, 2007.
[abs][pdf]

An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
Kwangmoo Koh, Seung-Jean Kim, Stephen Boyd; 8(Jul):1519--1555, 2007.
[abs][pdf]

Multi-class Protein Classification Using Adaptive Codes
Iain Melvin, Eugene Ie, Jason Weston, William Stafford Noble, Christina Leslie; 8(Jul):1557--1581, 2007.
[abs][pdf]

Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification
Onur C. Hamsici, Aleix M. Martinez; 8(Jul):1583--1623, 2007.
[abs][pdf]

Handling Missing Values when Applying Classification Models
Maytal Saar-Tsechansky, Foster Provost; 8(Jul):1623--1657, 2007.
[abs][pdf]

Compression-Based Averaging of Selective Naive Bayes Classifiers     (Special Topic on Model Selection)
Marc Boullé; 8(Jul):1659--1685, 2007.
[abs][pdf]

A Nonparametric Statistical Approach to Clustering via Mode Identification
Jia Li, Surajit Ray, Bruce G. Lindsay; 8(Aug):1687--1723, 2007.
[abs][pdf]

Polynomial Identification in the Limit of Substitutable Context-free Languages
Alexander Clark, Rémi Eyraud; 8(Aug):1725--1745, 2007.
[abs][pdf]

Structure and Majority Classes in Decision Tree Learning
Ray J. Hickey; 8(Aug):1747--1768, 2007.
[abs][pdf]

Characterizing the Function Space for Bayesian Kernel Models
Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert; 8(Aug):1769--1797, 2007.
[abs][pdf]

"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks
Gal Elidan, Iftach Nachman, Nir Friedman; 8(Aug):1799--1833, 2007.
[abs][pdf]

Behavioral Shaping for Geometric Concepts
Manu Chhabra, Robert A. Jacobs, Daniel Štefankovič; 8(Aug):1835--1865, 2007.
[abs][pdf]

Large Margin Semi-supervised Learning
Junhui Wang, Xiaotong Shen; 8(Aug):1867--1891, 2007.
[abs][pdf]

Fast Iterative Kernel Principal Component Analysis
Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan; 8(Aug):1893--1918, 2007.
[abs][pdf]

A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
Arindam Banerjee, Inderjit Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha; 8(Aug):1919--1986, 2007.
[abs][pdf]

Truncating the Loop Series Expansion for Belief Propagation
Vicenç Gómez, Joris M. Mooij, Hilbert J. Kappen; 8(Sep):1987--2016, 2007.
[abs][pdf]

Very Fast Online Learning of Highly Non Linear Problems
Aggelos Chariatis; 8(Sep):2017--2045, 2007.
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Unlabeled Compression Schemes for Maximum Classes
Dima Kuzmin, Manfred K. Warmuth; 8(Sep):2047--2081, 2007.
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Refinable Kernels
Yuesheng Xu, Haizhang Zhang; 8(Sep):2083--2120, 2007.
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A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion
Marco Loog; 8(Sep):2121--2123, 2007.
[abs][pdf]

Transfer Learning via Inter-Task Mappings for Temporal Difference Learning
Matthew E. Taylor, Peter Stone, Yaxin Liu; 8(Sep):2125--2167, 2007.
[abs][pdf]

Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes
Sridhar Mahadevan, Mauro Maggioni; 8(Oct):2169--2231, 2007.
[abs][pdf]

Online Learning of Multiple Tasks with a Shared Loss
Ofer Dekel, Philip M. Long, Yoram Singer; 8(Oct):2233--2264, 2007.
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Euclidean Embedding of Co-occurrence Data
Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby; 8(Oct):2265--2295, 2007.
[abs][pdf]

Harnessing the Expertise of 70,000 Human Editors: Knowledge-Based Feature Generation for Text Categorization
Evgeniy Gabrilovich, Shaul Markovitch; 8(Oct):2297--2345, 2007.
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AdaBoost is Consistent
Peter L. Bartlett, Mikhail Traskin; 8(Oct):2347--2368, 2007.
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The On-Line Shortest Path Problem Under Partial Monitoring
András György, Tamás Linder, Gábor Lugosi, György Ottucsák; 8(Oct):2369--2403, 2007.
[abs][pdf]

The Locally Weighted Bag of Words Framework for Document Representation
Guy Lebanon, Yi Mao, Joshua Dillon; 8(Oct):2405--2441, 2007.
[abs][pdf]

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; 8(Oct):2443--2466, 2007.
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On the Representer Theorem and Equivalent Degrees of Freedom of SVR
Francesco Dinuzzo, Marta Neve, Giuseppe De Nicolao, Ugo Pietro Gianazza; 8(Oct):2467--2495, 2007.
[abs][pdf]

Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
Ping Li, Trevor J. Hastie, Kenneth W. Church; 8(Oct):2497--2532, 2007.
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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; 8(Nov):2533--2549, 2007.
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VC Theory of Large Margin Multi-Category Classifiers     (Special Topic on Model Selection)
Yann Guermeur; 8(Nov):2551--2594, 2007.
[abs][pdf]

Learning in Environments with Unknown Dynamics: Towards more Robust Concept Learners
Marlon Núñez, Raúl Fidalgo, Rafael Morales; 8(Nov):2595--2628, 2007.
[abs][pdf]

Hierarchical Average Reward Reinforcement Learning
Mohammad Ghavamzadeh, Sridhar Mahadevan; 8(Nov):2629--2669, 2007.
[abs][pdf]

Ranking the Best Instances
Stéphan Clémençon, Nicolas Vayatis; 8(Dec):2671--2699, 2007.
[abs][pdf]

Stagewise Lasso
Peng Zhao, Bin Yu; 8(Dec):2701--2726, 2007.
[abs][pdf]

A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning     (Special Topic on Model Selection)
Carine Hue, Marc Boullé; 8(Dec):2727--2754, 2007.
[abs][pdf]

Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
J. Zico Kolter, Marcus A. Maloof; 8(Dec):2755--2790, 2007.
[abs][pdf]




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