JMLR 2008

91 papers

A Bahadur Representation of the Linear Support Vector Machine Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim, Changyi Park

A Moment Bound for Multi-Hinge Classifiers Bernadetta Tarigan, Sara A. van de Geer

A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters Zach Jorgensen, Yan Zhou, Meador Inge

A New Algorithm for Estimating the Effective Dimension-Reduction Subspace Arnak S. Dalalyan, Anatoly Juditsky, Vladimir Spokoiny

A Recursive Method for Structural Learning of Directed Acyclic Graphs Xianchao Xie, Zhi Geng

A Tutorial on Conformal Prediction Glenn Shafer, Vladimir Vovk

Accelerated Neural Evolution Through Cooperatively Coevolved Synapses Faustino Gomez, Jürgen Schmidhuber, Risto Miikkulainen

Active Learning by Spherical Subdivision Falk-Florian Henrich, Klaus Obermayer

Active Learning of Causal Networks with Intervention Experiments and Optimal Designs Yang-Bo He, Zhi Geng

Aggregation of SVM Classifiers Using Sobolev Spaces Sébastien Loustau

Algorithms for Sparse Linear Classifiers in the Massive Data Setting Suhrid Balakrishnan, David Madigan

An Error Bound Based on a Worst Likely Assignment Eric Bax, Augusto Callejas

An Extension on “Statistical Comparisons of Classifiers over Multiple Data Sets” for All Pairwise Comparisons Salvador García, Francisco Herrera

An Information Criterion for Variable Selection in Support Vector Machines Gerda Claeskens, Christophe Croux, Johan Van Kerckhoven

Approximations for Binary Gaussian Process Classification Hannes Nickisch, Carl Edward Rasmussen

Automatic PCA Dimension Selection for High Dimensional Data and Small Sample Sizes David C. Hoyle

Bayesian Inference and Optimal Design for the Sparse Linear Model Matthias W. Seeger

Bouligand Derivatives and Robustness of Support Vector Machines for Regression Andreas Christmann, Arnout Van Messem

Causal Reasoning with Ancestral Graphs Jiji Zhang

Classification with a Reject Option Using a Hinge Loss Peter L. Bartlett, Marten H. Wegkamp

Closed Sets for Labeled Data Gemma C. Garriga, Petra Kralj, Nada Lavrač

Comments on the Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion Jieping Ye

Complete Identification Methods for the Causal Hierarchy Ilya Shpitser, Judea Pearl

Consistency of Random Forests and Other Averaging Classifiers Gérard Biau, Luc Devroye, Gábor Lugosi

Consistency of the Group Lasso and Multiple Kernel Learning Francis R. Bach

Consistency of Trace Norm Minimization Francis R. Bach

Coordinate Descent Method for Large-Scale L2-Loss Linear Support Vector Machines Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin

Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods Matthias W. Seeger

Discriminative Learning of Max-Sum Classifiers Vojtěch Franc, Bogdan Savchynskyy

Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen

Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers Bo Jiang, Xuegong Zhang, Tianxi Cai

Evidence Contrary to the Statistical View of Boosting David Mease, Abraham Wyner

Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks Michael Collins, Amir Globerson, Terry Koo, Xavier Carreras, Peter L. Bartlett

Finding Optimal Bayesian Network Given a Super-Structure Eric Perrier, Seiya Imoto, Satoru Miyano

Finite-Time Bounds for Fitted Value Iteration Rémi Munos, Csaba Szepesvári

Forecasting Web Page Views: Methods and Observations Jia Li, Andrew W. Moore

Generalization from Observed to Unobserved Features by Clustering Eyal Krupka, Naftali Tishby

Gradient Tree Boosting for Training Conditional Random Fields Thomas G. Dietterich, Guohua Hao, Adam Ashenfelter

Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models Mathias Drton, Thomas S. Richardson

Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns Shann-Ching Chen, Geoffrey J. Gordon, Robert F. Murphy

Hit Miss Networks with Applications to Instance Selection Elena Marchiori

HPB: A Model for Handling BN Nodes with High Cardinality Parents Jorge Jambeiro Filho, Jacques Wainer

Incremental Identification of Qualitative Models of Biological Systems Using Inductive Logic Programming Ashwin Srinivasan, Ross D. King

Learning Balls of Strings from Edit Corrections Leonor Becerra-Bonache, Colin de la Higuera, Jean-Christophe Janodet, Frédéric Tantini

Learning Bounded Treewidth Bayesian Networks Gal Elidan, Stephen Gould

Learning Control Knowledge for Forward Search Planning Sungwook Yoon, Alan Fern, Robert Givan

Learning from Multiple Sources Koby Crammer, Michael Kearns, Jennifer Wortman

Learning Reliable Classifiers from Small or Incomplete Data Sets: The Naive Credal Classifier 2 Giorgio Corani, Marco Zaffalon

Learning Similarity with Operator-Valued Large-Margin Classifiers Andreas Maurer

Learning to Combine Motor Primitives via Greedy Additive Regression Manu Chhabra, Robert A. Jacobs

Learning to Select Features Using Their Properties Eyal Krupka, Amir Navot, Naftali Tishby

Linear-Time Computation of Similarity Measures for Sequential Data Konrad Rieck, Pavel Laskov

Magic Moments for Structured Output Prediction Elisa Ricci, Tijl De Bie, Nello Cristianini

Manifold Learning: The Price of Normalization Yair Goldberg, Alon Zakai, Dan Kushnir, Ya'acov Ritov

Max-Margin Classification of Data with Absent Features Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller

Maximal Causes for Non-Linear Component Extraction Jörg Lücke, Maneesh Sahani

Minimal Nonlinear Distortion Principle for Nonlinear Independent Component Analysis Kun Zhang, Laiwan Chan

Mixed Membership Stochastic Blockmodels Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing

Model Selection for Regression with Continuous Kernel Functions Using the Modulus of Continuity Imhoi Koo, Rhee Man Kil

Model Selection in Kernel Based Regression Using the Influence Function Michiel Debruyne, Mia Hubert, Johan A.K. Suykens

Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont

Multi-Agent Reinforcement Learning in Common Interest and Fixed Sum Stochastic Games: An Experimental Study Avraham Bab, Ronen I. Brafman

Multi-Class Discriminant Kernel Learning via Convex Programming Jieping Ye, Shuiwang Ji, Jianhui Chen

Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies Andreas Krause, Ajit Singh, Carlos Guestrin

Nearly Uniform Validation Improves Compression-Based Error Bounds Eric Bax

Non-Parametric Modeling of Partially Ranked Data Guy Lebanon, Yi Mao

On Relevant Dimensions in Kernel Feature Spaces Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller

On the Equivalence of Linear Dimensionality-Reducing Transformations Marco Loog

On the Size and Recovery of Submatrices of Ones in a Random Binary Matrix Xing Sun, Andrew B. Nobel

On the Suitable Domain for SVM Training in Image Coding Gustavo Camps-Valls, Juan Gutiérrez, Gabriel Gómez-Pérez, Jesús Malo

Online Learning of Complex Prediction Problems Using Simultaneous Projections Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer

Optimal Solutions for Sparse Principal Component Analysis Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui

Optimization Techniques for Semi-Supervised Support Vector Machines Olivier Chapelle, Vikas Sindhwani, Sathiya S. Keerthi

Probabilistic Characterization of Random Decision Trees Amit Dhurandhar, Alin Dobra

Randomized Online PCA Algorithms with Regret Bounds That Are Logarithmic in the Dimension Manfred K. Warmuth, Dima Kuzmin

Ranking Categorical Features Using Generalization Properties Sivan Sabato, Shai Shalev-Shwartz

Ranking Individuals by Group Comparisons Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng

Regularization on Graphs with Function-Adapted Diffusion Processes Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman

Robust Submodular Observation Selection Andreas Krause, H. Brendan McMahan, Carlos Guestrin, Anupam Gupta

Search for Additive Nonlinear Time Series Causal Models Tianjiao Chu, Clark Glymour

SimpleMKL Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet

Stationary Features and Cat Detection François Fleuret, Donald Geman

Structural Learning of Chain Graphs via Decomposition Zongming Ma, Xianchao Xie, Zhi Geng

Support Vector Machinery for Infinite Ensemble Learning Hsuan-Tien Lin, Ling Li

Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective Liviu Panait, Karl Tuyls, Sean Luke

Trust Region Newton Method for Logistic Regression Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi

Universal Multi-Task Kernels Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying

Using Markov Blankets for Causal Structure Learning Jean-Philippe Pellet, André Elisseeff

Value Function Approximation Using Multiple Aggregation for Multiattribute Resource Management Abraham George, Warren B. Powell, Sanjeev R. Kulkarni

Value Function Based Reinforcement Learning in Changing Markovian Environments Balázs Csanád Csáji, László Monostori

Visualizing Data Using T-SNE Laurens van der Maaten, Geoffrey Hinton