JMLR 2008

95 papers

Structural Learning of Chain Graphs via Decomposition

Zongming Ma, Xianchao Xie, Zhi Geng

Magic Moments for Structured Output Prediction

Elisa Ricci, Tijl De Bie, Nello Cristianini

Robust Submodular Observation Selection

Andreas Krause, H. Brendan McMahan, Carlos Guestrin, Anupam Gupta

Automatic PCA Dimension Selection for High Dimensional Data and Small Sample Sizes

David C. Hoyle

Learning Bounded Treewidth Bayesian Networks

Gal Elidan, Stephen Gould

JNCC2: The Java Implementation Of Naive Credal Classifier 2

Giorgio Corani, Marco Zaffalon

An Extension on “Statistical Comparisons of Classifiers over Multiple Data Sets” for all Pairwise Comparisons

Salvador García, Francisco Herrera

Multi-Agent Reinforcement Learning in Common Interest and Fixed Sum Stochastic Games: An Experimental Study

Avraham Bab, Ronen I. Brafman

Model Selection for Regression with Continuous Kernel Functions Using the Modulus of Continuity

Imhoi Koo, Rhee Man Kil

Visualizing Data using t-SNE

Laurens van der Maaten, Geoffrey Hinton

Stationary Features and Cat Detection

Francois Fleuret, Donald Geman

Active Learning of Causal Networks with Intervention Experiments and Optimal Designs

Yang-Bo He, Zhi Geng

SimpleMKL

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

On the Equivalence of Linear Dimensionality-Reducing Transformations

Marco Loog

Minimal Nonlinear Distortion Principle for Nonlinear Independent Component Analysis

Kun Zhang, Laiwan Chan

On the Size and Recovery of Submatrices of Ones in a Random Binary Matrix

Xing Sun, Andrew B. Nobel

Non-Parametric Modeling of Partially Ranked Data

Guy Lebanon, Yi Mao

Model Selection in Kernel Based Regression using the Influence Function

Michiel Debruyne, Mia Hubert, Johan A.K. Suykens

Learning to Select Features using their Properties

Eyal Krupka, Amir Navot, Naftali Tishby

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

Finding Optimal Bayesian Network Given a Super-Structure

Eric Perrier, Seiya Imoto, Satoru Miyano

Forecasting Web Page Views: Methods and Observations

Jia Li, Andrew W. Moore

Ranking Individuals by Group Comparisons

Tzu-kuo Huang, Chih-Jen Lin, Ruby C. Weng

A Moment Bound for Multi-hinge Classifiers

Bernadetta Tarigan, Sara A. van de Geer

HPB: A Model for Handling BN Nodes with High Cardinality Parents

Jorge Jambeiro Filho, Jacques Wainer

Gradient Tree Boosting for Training Conditional Random Fields

Thomas G. Dietterich, Guohua Hao, Adam Ashenfelter

Value Function Approximation using Multiple Aggregation for Multiattribute Resource Management

Abraham George, Warren B. Powell, Sanjeev R. Kulkarni

Approximations for Binary Gaussian Process Classification

Hannes Nickisch, Carl Edward Rasmussen

Consistency of Random Forests and Other Averaging Classifiers

Gérard Biau, Luc Devroye, Gabor Lugosi

Mixed Membership Stochastic Blockmodels

Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing

Complete Identification Methods for the Causal Hierarchy

Ilya Shpitser, Judea Pearl

Manifold Learning: The Price of Normalization

Yair Goldberg, Alon Zakai, Dan Kushnir, Ya'acov Ritov

On Relevant Dimensions in Kernel Feature Spaces

Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller

LIBLINEAR: A Library for Large Linear Classification

Rong-En Fan, Kai-Wei Chang, Cho-jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin

Learning Balls of Strings from Edit Corrections

Leonor Becerra-Bonache, Colin de la Higuera, Jean-Christophe Janodet, Frédéric Tantini

Classification with a Reject Option using a Hinge Loss

Peter L. Bartlett, Marten H. Wegkamp

Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks

Michael Collins, Amir Globerson, Terry Koo, Xavier Carreras, Peter L. Bartlett

Learning from Multiple Sources

Koby Crammer, Michael Kearns, Jennifer Wortman

Nearly Uniform Validation Improves Compression-Based Error Bounds

Eric Bax

Regularization on Graphs with Function-adapted Diffusion Processes

Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman

Value Function Based Reinforcement Learning in Changing Markovian Environments

Balázs Csanád Csáji, László Monostori

A New Algorithm for Estimating the Effective Dimension-Reduction Subspace

Arnak S. Dalalyan, Anatoly Juditsky, Vladimir Spokoiny

Universal Multi-Task Kernels

Andrea Caponnetto, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying

Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction

Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen

Aggregation of SVM Classifiers Using Sobolev Spaces

Sébastien Loustau

Learning to Combine Motor Primitives Via Greedy Additive Regression

Manu Chhabra, Robert A. Jacobs

Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming

Ashwin Srinivasan, Ross D. King

Causal Reasoning with Ancestral Graphs

Jiji Zhang

Online Learning of Complex Prediction Problems Using Simultaneous Projections

Yonatan Amit, Shai Shalev-shwartz, Yoram Singer

Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines

Kai-Wei Chang, Cho-jui Hsieh, Chih-Jen Lin

A Bahadur Representation of the Linear Support Vector Machine

Ja-Yong Koo, Yoonkyung Lee, Yuwon Kim, Changyi Park

Using Markov Blankets for Causal Structure Learning

Jean-philippe Pellet, André Elisseeff

Optimal Solutions for Sparse Principal Component Analysis

Alexandre D'aspremont, Francis Bach, Laurent El Ghaoui

Maximal Causes for Non-linear Component Extraction

Jörg Lücke, Maneesh Sahani

Consistency of the Group Lasso and Multiple Kernel Learning

Francis R. Bach

Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods

Matthias W. Seeger

A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters

Zach Jorgensen, Yan Zhou, Meador Inge

Ranking Categorical Features Using Generalization Properties

Sivan Sabato, Shai Shalev-shwartz

Andreas Maurer

Consistency of Trace Norm Minimization

Francis R. Bach

Hit Miss Networks with Applications to Instance Selection

Elena Marchiori

Shark

Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers

Search for Additive Nonlinear Time Series Causal Models

Tianjiao Chu, Clark Glymour

Accelerated Neural Evolution through Cooperatively Coevolved Synapses

Faustino Gomez, Jürgen Schmidhuber, Risto Miikkulainen

Bouligand Derivatives and Robustness of Support Vector Machines for Regression

Andreas Christmann, Arnout Van Messem

Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models

Mathias Drton, Thomas S. Richardson

An Error Bound Based on a Worst Likely Assignment

Eric Bax, Augusto Callejas

Finite-Time Bounds for Fitted Value Iteration

Rémi Munos, Csaba Szepesvári

Bayesian Inference and Optimal Design for the Sparse Linear Model

Matthias W. Seeger

Multi-class Discriminant Kernel Learning via Convex Programming

Jieping Ye, Shuiwang Ji, Jianhui Chen

Learning Control Knowledge for Forward Search Planning

Sungwook Yoon, Alan Fern, Robert Givan

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

Trust Region Newton Method for Logistic Regression

Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi

A Library for Locally Weighted Projection Regression

Stefan Klanke, Sethu Vijayakumar, Stefan Schaal

Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2

Giorgio Corani, Marco Zaffalon

Closed Sets for Labeled Data

Gemma C. Garriga, Petra Kralj, Nada Lavra&#269

An Information Criterion for Variable Selection in Support Vector Machines

Gerda Claeskens, Christophe Croux, Johan Van Kerckhoven

Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers

Bo Jiang, Xuegong Zhang, Tianxi Cai

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

Jieping Ye

Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data

Onureena Banerjee, Laurent El Ghaoui, Alexandre D'aspremont

A Recursive Method for Structural Learning of Directed Acyclic Graphs

Xianchao Xie, Zhi Geng

Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective

Liviu Panait, Karl Tuyls, Sean Luke

A Tutorial on Conformal Prediction

Glenn Shafer, Vladimir Vovk

Generalization from Observed to Unobserved Features by Clustering

Eyal Krupka, Naftali Tishby

Algorithms for Sparse Linear Classifiers in the Massive Data Setting

Suhrid Balakrishnan, David Madigan

Support Vector Machinery for Infinite Ensemble Learning

Hsuan-tien Lin, Ling Li

Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies

Andreas Krause, Ajit Singh, Carlos Guestrin

Optimization Techniques for Semi-Supervised Support Vector Machines

Olivier Chapelle, Vikas Sindhwani, Sathiya S. Keerthi

Evidence Contrary to the Statistical View of Boosting

David Mease, Abraham Wyner

Active Learning by Spherical Subdivision

Falk-Florian Henrich, Klaus Obermayer

Discriminative Learning of Max-Sum Classifiers

Vojtěch Franc, Bogdan Savchynskyy

On the Suitable Domain for SVM Training in Image Coding

Gustavo Camps-Valls, Juan Gutiérrez, Gabriel Gómez-Pérez, Jesus Malo

Linear-Time Computation of Similarity Measures for Sequential Data

Konrad Rieck, Pavel Laskov

Max-margin Classification of Data with Absent Features

Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller