ML Anthology

JMLR 2007

91 papers

"Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks Gal Elidan, Iftach Nachman, Nir Friedman
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A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion Marco Loog
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A Generalized Maximum Entropy Approach to Bregman Co-Clustering and Matrix Approximation Arindam Banerjee, Inderjit Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha
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A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning Carine Hue, Marc Boullé
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A Nonparametric Statistical Approach to Clustering via Mode Identification Jia Li, Surajit Ray, Bruce G. Lindsay
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A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians Sanjoy Dasgupta, Leonard Schulman
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A Stochastic Algorithm for Feature Selection in Pattern Recognition Sébastien Gadat, Laurent Younes
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A Unified Continuous Optimization Framework for Center-Based Clustering Methods Marc Teboulle
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AdaBoost Is Consistent Peter L. Bartlett, Mikhail Traskin
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An Interior-Point Method for Large-Scale L1-Regularized Logistic Regression Kwangmoo Koh, Seung-Jean Kim, Stephen Boyd
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Anytime Learning of Decision Trees Saher Esmeir, Shaul Markovitch
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Attribute-Efficient and Non-Adaptive Learning of Parities and DNF Expressions Vitaly Feldman
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Bayesian Quadratic Discriminant Analysis Santosh Srivastava, Maya R. Gupta, Béla A. Frigyik
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Behavioral Shaping for Geometric Concepts Manu Chhabra, Robert A. Jacobs, Daniel Štefankovič
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Bilinear Discriminant Component Analysis Mads Dyrholm, Christoforos Christoforou, Lucas C. Parra
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Boosted Classification Trees and Class Probability/Quantile Estimation David Mease, Abraham J. Wyner, Andreas Buja
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Building Blocks for Variational Bayesian Learning of Latent Variable Models Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen
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Characterizing the Function Space for Bayesian Kernel Models Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert
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Classification in Networked Data: A Toolkit and a Univariate Case Study Sofus A. Macskassy, Foster Provost
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Combining PAC-Bayesian and Generic Chaining Bounds Jean-Yves Audibert, Olivier Bousquet
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Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets" Gaëlle Loosli, Stéphane Canu
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Compression-Based Averaging of Selective Naive Bayes Classifiers Marc Boullé
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Concave Learners for Rankboost Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang
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Consistent Feature Selection for Pattern Recognition in Polynomial Time Roland Nilsson, José M. Peña, Johan Björkegren, Jesper Tegnér
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Covariate Shift Adaptation by Importance Weighted Cross Validation Masashi Sugiyama, Matthias Krauledat, Klaus-Robert Müller
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Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis Masashi Sugiyama
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Distances Between Data Sets Based on Summary Statistics Nikolaj Tatti
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Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data Charles Sutton, Andrew McCallum, Khashayar Rohanimanesh
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Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts J. Zico Kolter, Marcus A. Maloof
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Dynamics and Generalization Ability of LVQ Algorithms Michael Biehl, Anarta Ghosh, Barbara Hammer
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Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm Markus Kalisch, Peter Bühlmann
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Euclidean Embedding of Co-Occurrence Data Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby
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Fast Iterative Kernel Principal Component Analysis Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan
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From External to Internal Regret Avrim Blum, Yishay Mansour
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General Polynomial Time Decomposition Algorithms Nikolas List, Hans Ulrich Simon
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Generalization Error Bounds in Semi-Supervised Classification Under the Cluster Assumption Philippe Rigollet
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Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression Shantanu Chakrabartty, Gert Cauwenberghs
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Graph Laplacians and Their Convergence on Random Neighborhood Graphs Matthias Hein, Jean-Yves Audibert, Ulrike von Luxburg
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Handling Missing Values When Applying Classification Models Maytal Saar-Tsechansky, Foster Provost
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Harnessing the Expertise of 70,000 Human Editors: Knowledge-Based Feature Generation for Text Categorization Evgeniy Gabrilovich, Shaul Markovitch
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Hierarchical Average Reward Reinforcement Learning Mohammad Ghavamzadeh, Sridhar Mahadevan
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Infinitely Imbalanced Logistic Regression Art B. Owen
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Integrating Naïve Bayes and FOIL Niels Landwehr, Kristian Kersting, Luc De Raedt
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Large Margin Semi-Supervised Learning Junhui Wang, Xiaotong Shen
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Learnability of Gaussians with Flexible Variances Yiming Ying, Ding-Xuan Zhou
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Learning Equivariant Functions with Matrix Valued Kernels Marco Reisert, Hans Burkhardt
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Learning Horn Expressions with LOGAN-H Marta Arias, Roni Khardon, Jérôme Maloberti
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Learning in Environments with Unknown Dynamics: Towards More Robust Concept Learners Marlon Núñez, Raúl Fidalgo, Rafael Morales
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Learning to Classify Ordinal Data: The Data Replication Method Jaime S. Cardoso, Joaquim F. Pinto da Costa
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Local Discriminant Wavelet Packet Coordinates for Face Recognition Chao-Chun Liu, Dao-Qing Dai, Hong Yan
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Loop Corrections for Approximate Inference on Factor Graphs Joris M. Mooij, Hilbert J. Kappen
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Margin Trees for High-Dimensional Classification Robert Tibshirani, Trevor Hastie
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Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
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Measuring Differentiability: Unmasking Pseudonymous Authors Moshe Koppel, Jonathan Schler, Elisheva Bonchek-Dokow
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Minimax Regret Classifier for Imprecise Class Distributions Rocío Alaiz-Rodríguez, Alicia Guerrero-Curieses, Jesús Cid-Sueiro
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Multi-Class Protein Classification Using Adaptive Codes Iain Melvin, Eugene Ie, Jason Weston, William Stafford Noble, Christina Leslie
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Multi-Task Learning for Classification with Dirichlet Process Priors Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram
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Noise Tolerant Variants of the Perceptron Algorithm Roni Khardon, Gabriel Wachman
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Nonlinear Boosting Projections for Ensemble Construction Nicolás García-Pedrajas, César García-Osorio, Colin Fyfe
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Nonlinear Estimators and Tail Bounds for Dimension Reduction in L1 Using Cauchy Random Projections Ping Li, Trevor J. Hastie, Kenneth W. Church
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On the Consistency of Multiclass Classification Methods Ambuj Tewari, Peter L. Bartlett
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On the Effectiveness of Laplacian Normalization for Graph Semi-Supervised Learning Rie Johnson, Tong Zhang
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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
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Online Learning of Multiple Tasks with a Shared Loss Ofer Dekel, Philip M. Long, Yoram Singer
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PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers François Laviolette, Mario Marchand
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Penalized Model-Based Clustering with Application to Variable Selection Wei Pan, Xiaotong Shen
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Polynomial Identification in the Limit of Substitutable Context-Free Languages Alexander Clark, Rémi Eyraud
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Preventing Over-Fitting During Model Selection via Bayesian Regularisation of the Hyper-Parameters Gavin C. Cawley, Nicola L. C. Talbot
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Proto-Value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes Sridhar Mahadevan, Mauro Maggioni
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Ranking the Best Instances Stéphan Clémençon, Nicolas Vayatis
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Refinable Kernels Yuesheng Xu, Haizhang Zhang
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Relational Dependency Networks Jennifer Neville, David Jensen
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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
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Separating Models of Learning from Correlated and Uncorrelated Data Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andrew Wan
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Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results Peter L. Bartlett, Ambuj Tewari
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Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification Onur C. Hamsici, Aleix M. Martinez
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Stagewise Lasso Peng Zhao, Bin Yu
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Statistical Consistency of Kernel Canonical Correlation Analysis Kenji Fukumizu, Francis R. Bach, Arthur Gretton
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Structure and Majority Classes in Decision Tree Learning Ray J. Hickey
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Synergistic Face Detection and Pose Estimation with Energy-Based Models Margarita Osadchy, Yann Le Cun, Matthew L. Miller
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The Locally Weighted Bag of Words Framework for Document Representation Guy Lebanon, Yi Mao, Joshua Dillon
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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
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The On-Line Shortest Path Problem Under Partial Monitoring András György, Tamás Linder, Gábor Lugosi, György Ottucsák
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The Pyramid Match Kernel: Efficient Learning with Sets of Features Kristen Grauman, Trevor Darrell
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Transfer Learning via Inter-Task Mappings for Temporal Difference Learning Matthew E. Taylor, Peter Stone, Yaxin Liu
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Truncating the Loop Series Expansion for Belief Propagation Vicenç Gómez, Joris M. Mooij, Hilbert J. Kappen
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Undercomplete Blind Subspace Deconvolution Zoltán Szabó, Barnabás Póczos, András Lőrincz
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Unlabeled Compression Schemes for Maximum Classes Dima Kuzmin, Manfred K. Warmuth
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Value Regularization and Fenchel Duality Ryan M. Rifkin, Ross A. Lippert
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VC Theory of Large Margin Multi-Category Classifiers Yann Guermeur
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Very Fast Online Learning of Highly Non Linear Problems Aggelos Chariatis
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