MLJ 2001

48 papers

A Learning Generalization Bound with an Application to Sparse-Representation Classifiers Yoram Gat

A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems David J. Hand, Robert J. Till

Accelerating EM for Large Databases Bo Thiesson, Christopher Meek, David Heckerman

An Adaptive Version of the Boost by Majority Algorithm Yoav Freund

An Experimental Comparison of Model-Based Clustering Methods Marina Meila, David Heckerman

Approximate Match of Rules Using Backpropagation Neural Networks Boonserm Kijsirikul, Sukree Sinthupinyo, Kongsak Chongkasemwongse

Concept Decompositions for Large Sparse Text Data Using Clustering Inderjit S. Dhillon, Dharmendra S. Modha

Confirmation-Guided Discovery of First-Order Rules with Tertius Peter A. Flach, Nicolas Lachiche

Drifting Games Robert E. Schapire

Efficient Algorithms for the Inference of Minimum Size DFAs Arlindo L. Oliveira, João P. Marques Silva

Efficient Construction of Regression Trees with Range and Region Splitting Yasuhiko Morimoto, Hiromu Ishii, Shinichi Morishita

Extracting Context-Sensitive Models in Inductive Logic Programming Ashwin Srinivasan

General Convergence Results for Linear Discriminant Updates Adam J. Grove, Nick Littlestone, Dale Schuurmans

Introduction Douglas H. Fisher

Iterated Phantom Induction: A Knowledge-Based Approach to Learning Control Mark Brodie, Gerald DeJong

Language Simplification Through Error-Correcting and Grammatical Inference Techniques Juan-Carlos Amengual, Alberto Sanchís, Enrique Vidal, José-Miguel Benedí

Learning DFA from Simple Examples Rajesh Parekh, Vasant G. Honavar

Learning Regular Languages from Simple Positive Examples François Denis

Learning with Maximum-Entropy Distributions Yishay Mansour, Mariano Schain

Linear Concepts and Hidden Variables Adam J. Grove, Dan Roth

Noisy Time Series Prediction Using Recurrent Neural Networks and Grammatical Inference C. Lee Giles, Steve Lawrence, Ah Chung Tsoi

On Exact Learning of Unordered Tree Patterns Thomas R. Amoth, Paul Cull, Prasad Tadepalli

On the Convergence of Temporal-Difference Learning with Linear Function Approximation Vladislav Tadic

On the VC Dimension of Bounded Margin Classifiers Don R. Hush, Clint Scovel

Optimizing Epochal Evolutionary Search: Population-Size Dependent Theory Erik van Nimwegen, James P. Crutchfield

Parameter Estimation in Stochastic Logic Programs James Cussens

Predicting the Future of Discrete Sequences from Fractal Representations of the past Peter Tiño, Georg Dorffner

Random Forests Leo Breiman

Reinterpreting the Category Utility Function Boris G. Mirkin

Relational Instance-Based Learning with Lists and Terms Tamás Horváth, Stefan Wrobel, Uta Bohnebeck

Relational Learning with Statistical Predicate Invention: Better Models for Hypertext Mark Craven, Seán Slattery

Relational Reinforcement Learning Saso Dzeroski, Luc De Raedt, Kurt Driessens

Relative Loss Bounds for Multidimensional Regression Problems Jyrki Kivinen, Manfred K. Warmuth

Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions Katy S. Azoury, Manfred K. Warmuth

Robust Classification for Imprecise Environments Foster J. Provost, Tom Fawcett

Robust Learning with Missing Data Marco Ramoni, Paola Sebastiani

Soft Margins for AdaBoost Gunnar Rätsch, Takashi Onoda, Klaus-Robert Müller

Some Statistical-Estimation Methods for Stochastic Finite-State Transducers David Picó, Francisco Casacuberta

SPADE: An Efficient Algorithm for Mining Frequent Sequences Mohammed Javeed Zaki

Stochastic Finite Learning of the Pattern Languages Peter Rossmanith, Thomas Zeugmann

Stochastic Inference of Regular Tree Languages Rafael C. Carrasco, José Oncina, Jorge Calera-Rubio

Supervised Versus Unsupervised Binary-Learning by Feedforward Neural Networks Nathalie Japkowicz

The Effect of Instance-Space Partition on Significance Jeffrey P. Bradford, Carla E. Brodley

The Effect of Relational Background Knowledge on Learning of Protein Three-Dimensional Fold Signatures Marcel Turcotte, Stephen H. Muggleton, Michael J. E. Sternberg

Unsupervised Learning by Probabilistic Latent Semantic Analysis Thomas Hofmann

Unsupervised Learning of Word Segmentation Rules with Genetic Algorithms and Inductive Logic Programming Dimitar Kazakov, Suresh Manandhar

Using Iterated Bagging to Debias Regressions Leo Breiman

Worst-Case Bounds for the Logarithmic Loss of Predictors Nicolò Cesa-Bianchi, Gábor Lugosi