MLJ 2005

42 papers

A Fast Dual Algorithm for Kernel Logistic Regression S. Sathiya Keerthi, Kaibo Duan, Shirish K. Shevade, Aun Neow Poo

A High Order Cumulants Based Multivariate Nonlinear Blind Source Separation Method Feng Zhang

A Neural Syntactic Language Model Ahmad Emami, Frederick Jelinek

A Reinforcement Learning Scheme for a Partially-Observable Multi-Agent Game Shin Ishii, Hajime Fujita, Masaoki Mitsutake, Tatsuya Yamazaki, Jun Matsuda, Yoichiro Matsuno

A Response to Webb and Ting's on the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions Tom Fawcett, Peter A. Flach

Automatic Feature Extraction for Classifying Audio Data Ingo Mierswa, Katharina Morik

Case Based Imprecision Estimates for Bayes Classifiers with the Bayesian Bootstrap G. Niklas Norén, Roland Orre

Classification of Multivariate Time Series and Structured Data Using Constructive Induction Mohammed Waleed Kadous, Claude Sammut

Clustering Time Series with Clipped Data Anthony J. Bagnall, Gareth J. Janacek

Combined SVM-Based Feature Selection and Classification Julia Neumann, Christoph Schnörr, Gabriele Steidl

Combining Statistical Language Models via the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

Corpus-Based Learning of Analogies and Semantic Relations Peter D. Turney, Michael L. Littman

Discovery of Time-Series Motif from Multi-Dimensional Data Based on MDL Principle Yoshiki Tanaka, Kazuhisa Iwamoto, Kuniaki Uehara

Elastic Translation Invariant Matching of Trajectories Michail Vlachos, George Kollios, Dimitrios Gunopulos

Evolutionary Rule Mining in Time Series Databases Magnus Lie Hetland, Pål Sætrom

Evolving Soccer Keepaway Players Through Task Decomposition Shimon Whiteson, Nate Kohl, Risto Miikkulainen, Peter Stone

Fast and Exact Warping of Time Series Using Adaptive Segmental Approximations Yutao Shou, Nikos Mamoulis, David W. Cheung

Filtering-Ranking Perceptron Learning for Partial Parsing Xavier Carreras, Lluís Màrquez, C. Jorge Castro

Generalized Low Rank Approximations of Matrices Jieping Ye

Incremental Learning of Linear Model Trees Duncan Potts, Claude Sammut

Internal Regret in On-Line Portfolio Selection Gilles Stoltz, Gábor Lugosi

Latent Classification Models Helge Langseth, Thomas D. Nielsen

Learning Bayesian Network Classifiers: Searching in a Space of Partially Directed Acyclic Graphs Silvia Acid, Luis M. de Campos, Francisco Javier García Castellano

Logistic Model Trees Niels Landwehr, Mark Hall, Eibe Frank

Maximizing Agreements with One-Sided Error with Applications to Heuristic Learning Nader H. Bshouty, Lynn Burroughs

Maximum Entropy Modeling: A Suitable Framework to Learn Context-Dependent Lexicon Models for Statistical Machine Translation Ismael García-Varea, Francisco Casacuberta

Maximum Entropy Models with Inequality Constraints: A Case Study on Text Categorization Jun'ichi Kazama, Jun'ichi Tsujii

Moment Kernels for Regular Distributions Corinna Cortes, Mehryar Mohri

Multicategory Proximal Support Vector Machine Classifiers Glenn Fung, Olvi L. Mangasarian

Not so Naive Bayes: Aggregating One-Dependence Estimators Geoffrey I. Webb, Janice R. Boughton, Zhihai Wang

On Discriminative Bayesian Network Classifiers and Logistic Regression Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri

On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions Geoffrey I. Webb, Kai Ming Ting

Online Multiclass Learning with K-Way Limited Feedback and an Application to Utterance Classification Hiyan Alshawi

PAC-Bayesian Compression Bounds on the Prediction Error of Learning Algorithms for Classification Thore Graepel, Ralf Herbrich, John Shawe-Taylor

Principle Components and Importance Ranking of Distributed Anomalies Kyrre M. Begnum, Mark Burgess

Ranking and Reranking with Perceptron Libin Shen, Aravind K. Joshi

ROC 'n' Rule Learning - Towards a Better Understanding of Covering Algorithms Johannes Fürnkranz, Peter A. Flach

Single-Class Classification with Mapping Convergence Hwanjo Yu

Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers Russell Greiner, Xiaoyuan Su, Bin Shen, Wei Zhou

Support Vector Learning for Semantic Argument Classification Sameer S. Pradhan, Kadri Hacioglu, Valerie Krugler, Wayne H. Ward, James H. Martin, Daniel Jurafsky

TAN Classifiers Based on Decomposable Distributions Jesús Cerquides, Ramón López de Mántaras

The Synergy Between PAV and AdaBoost W. John Wilbur, Lana Yeganova, Won Kim