MLJ 2011

56 papers

A Majorization-Minimization Approach to the Sparse Generalized Eigenvalue Problem Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet

Adaptive Partitioning Schemes for Bipartite Ranking - How to Grow and Prune a Ranking Tree Stéphan Clémençon, Marine Depecker, Nicolas Vayatis

An Asymptotically Optimal Policy for Finite Support Models in the Multiarmed Bandit Problem Junya Honda, Akimichi Takemura

An Experimental Test of Occam's Razor in Classification Jan Zahálka, Filip Zelezný

Anytime Learning of Anycost Classifiers Saher Esmeir, Shaul Markovitch

Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy Ondrej Kuzelka, Filip Zelezný

Boosted Multi-Task Learning Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng

Characterizing Reinforcement Learning Methods Through Parameterized Learning Problems Shivaram Kalyanakrishnan, Peter Stone

Checkpoint Evolution for Volatile Correlation Computing Wenjun Zhou, Hui Xiong

Classifier Chains for Multi-Label Classification Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank

Constraint-Based Probabilistic Modeling for Statistical Abduction Taisuke Sato, Masakazu Ishihata, Katsumi Inoue

Construction and Learnability of Canonical Horn Formulas Marta Arias, José L. Balcázar

Creating Non-Minimal Triangulations for Use in Inference in Mixed Stochastic/deterministic Graphical Models Chris D. Bartels, Jeff A. Bilmes

Detecting Communities and Their Evolutions in Dynamic Social Networks - A Bayesian Approach Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin

Dual Coordinate Descent Methods for Logistic Regression and Maximum Entropy Models Hsiang-Fu Yu, Fang-Lan Huang, Chih-Jen Lin

Editorial Survey: Swarm Intelligence for Data Mining David Martens, Bart Baesens, Tom Fawcett

Effective Feature Construction by Maximum Common Subgraph Sampling Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt

Efficient Mining for Structurally Diverse Subgraph Patterns in Large Molecular Databases Andreas Maunz, Christoph Helma, Stefan Kramer

Efficiently Mining Δ-Tolerance Closed Frequent Subgraphs Ichigaku Takigawa, Hiroshi Mamitsuka

Empirical Evaluation Methods for Multiobjective Reinforcement Learning Algorithms Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker

Estimating Variable Structure and Dependence in Multitask Learning via Gradients Justin Guinney, Qiang Wu, Sayan Mukherjee

Feature-Subspace Aggregating: Ensembles for Stable and Unstable Learners Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb

Foraging Theory for Dimensionality Reduction of Clustered Data Luis Felipe Giraldo, Fernando Lozano, Nicanor Quijano

Guest Editorial to the Special Issue on Inductive Logic Programming, Mining and Learning in Graphs and Statistical Relational Learning Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan

Inductive Equivalence in Clausal Logic and Nonmonotonic Logic Programming Chiaki Sakama, Katsumi Inoue

Informing Sequential Clinical Decision-Making Through Reinforcement Learning: An Empirical Study Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte, T. Scott Stroup, Joelle Pineau, Susan A. Murphy

Introduction to the Special Issue on Empirical Evaluations in Reinforcement Learning Shimon Whiteson, Michael L. Littman

Iterative Learning from Texts and Counterexamples Using Additional Information Sanjay Jain, Efim B. Kinber

Knows What It Knows: A Framework for Self-Aware Learning Lihong Li, Michael L. Littman, Thomas J. Walsh, Alexander L. Strehl

Languages as Hyperplanes: Grammatical Inference with String Kernels Alexander Clark, Christophe Costa Florêncio, Chris Watkins

Learning Noisy Linear Classifiers via Adaptive and Selective Sampling Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile

Learning to Compete, Coordinate, and Cooperate in Repeated Games Using Reinforcement Learning Jacob W. Crandall, Michael A. Goodrich

Machine Learning in Space: Extending Our Reach Amy McGovern, Kiri L. Wagstaff

Model Selection for Primal SVM Gregory M. Moore, Charles Bergeron, Kristin P. Bennett

Model Selection in Reinforcement Learning Amir Massoud Farahmand, Csaba Szepesvári

Multi-Way Set Enumeration in Weight Tensors Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf

Neural Networks for Relational Learning: An Experimental Comparison Werner Uwents, Gabriele Monfardini, Hendrik Blockeel, Marco Gori, Franco Scarselli

Non-Homogeneous Dynamic Bayesian Networks for Continuous Data Marco Grzegorczyk, Dirk Husmeier

On the Analysis and Design of Software for Reinforcement Learning, with a Survey of Existing Systems Tim Kovacs, Robert Egginton

Onboard Object Recognition for Planetary Exploration Michael C. Burl, Philipp Georg Wetzler

Particle Swarm Optimizer for Variable Weighting in Clustering High-Dimensional Data Yanping Lu, Shengrui Wang, Shaozi Li, Changle Zhou

Policy Search for Motor Primitives in Robotics Jens Kober, Jan Peters

Reinforcement Learning in Feedback Control - Challenges and Benchmarks from Technical Process Control Roland Hafner, Martin A. Riedmiller

Relational Information Gain Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andrea Passerini

Resampling Approach for Cluster Model Selection Zeev Volkovich, Zeev Barzily, Gerhard-Wilhelm Weber, Dvora Toledano-Kitai, Renata Avros

Sparse Canonical Correlation Analysis David R. Hardoon, John Shawe-Taylor

Sparse Conjugate Directions Pursuit with Application to Fixed-Size Kernel Models Peter Karsmakers, Kristiaan Pelckmans, Kris De Brabanter, Hugo Van hamme, Johan A. K. Suykens

SpicyMKL: A Fast Algorithm for Multiple Kernel Learning with Thousands of Kernels Taiji Suzuki, Ryota Tomioka

Statistical Relational Learning of Trust Achim Rettinger, Matthias Nickles, Volker Tresp

Stochastic Relational Processes: Efficient Inference and Applications Ingo Thon, Niels Landwehr, Luc De Raedt

Ternary Bradley-Terry Model-Based Decoding for Multi-Class Classification and Its Extensions Takashi Takenouchi, Shin Ishii

The Changing Science of Machine Learning Pat Langley

The First Learning Track of the International Planning Competition Alan Fern, Roni Khardon, Prasad Tadepalli

The Machine Learning Journal: 25 Years Young Peter A. Flach

The Optimal Unbiased Value Estimator and Its Relation to LSTD, TD and MC Steffen Grünewälder, Klaus Obermayer

Topic Level Expertise Search over Heterogeneous Networks Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, Zhong Su