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ORCID18th ICML 2001: Williams College, Williamstown, MA, USA
- Carla E. Brodley, Andrea Pohoreckyj Danyluk:
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001. Morgan Kaufmann 2001, ISBN 1-55860-778-1 - Robert A. Amar, Daniel R. Dooly, Sally A. Goldman, Qi Zhang:
Multiple-Instance Learning of Real-Valued Data. ICML 2001: 3-10 - Hendrik Blockeel, Jan Struyf:
Efficient algorithms for decision tree cross-validation. ICML 2001: 11-18 - Avrim Blum, Shuchi Chawla:
Learning from Labeled and Unlabeled Data using Graph Mincuts. ICML 2001: 19-26 - Michael H. Bowling, Manuela M. Veloso:
Convergence of Gradient Dynamics with a Variable Learning Rate. ICML 2001: 27-34 - Urszula Chajewska, Daphne Koller, Dirk Ormoneit:
Learning an Agent's Utility Function by Observing Behavior. ICML 2001: 35-42 - David Choi, Benjamin Van Roy:
A Generalized Kalman Filter for Fixed Point Approximation and Efficient Temporal Difference Learning. ICML 2001: 43-50 - Wei Chu, S. Sathiya Keerthi, Chong Jin Ong:
A Unified Loss Function in Bayesian Framework for Support Vector Regression. ICML 2001: 51-58 - Craig W. Codrington:
Boosting with Confidence Information. ICML 2001: 59-65 - Nello Cristianini, John Shawe-Taylor, Huma Lodhi:
Latent Semantic Kernels. ICML 2001: 66-73 - Sanmay Das:
Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection. ICML 2001: 74-81 - Richard Dearden:
Structured Prioritised Sweeping. ICML 2001: 82-89 - Alin Dobra, Johannes Gehrke:
Bias Correction in Classification Tree Construction. ICML 2001: 90-97 - Carlotta Domeniconi, Dimitrios Gunopulos:
An Efficient Approach for Approximating Multi-dimensional Range Queries and Nearest Neighbor Classification in Large Datasets. ICML 2001: 98-105 - Pedro M. Domingos, Geoff Hulten:
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering. ICML 2001: 106-113 - Melissa Dominguez, Robert A. Jacobs:
Visual Development and the Acquisition of Binocular Disparity Sensitivities. ICML 2001: 114-121 - Harris Drucker, Behzad Shahraray, David C. Gibbon:
Relevance Feedback using Support Vector Machines. ICML 2001: 122-129 - Tina Eliassi-Rad, Jude W. Shavlik:
A Theory-Refinement Approach to Information Extraction. ICML 2001: 130-137 - Yaakov Engel, Shie Mannor:
Learning Embedded Maps of Markov Processes. ICML 2001: 138-145 - Johannes Fürnkranz:
Round Robin Rule Learning. ICML 2001: 146-153 - Thomas Gärtner, Peter A. Flach:
WBCsvm: Weighted Bayesian Classification based on Support Vector Machines. ICML 2001: 154-161 - Peter Geibel:
Reinforcement Learning with Bounded Risk. ICML 2001: 162-169 - Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar:
Learning Probabilistic Models of Relational Structure. ICML 2001: 170-177 - Rayid Ghani, Seán Slattery, Yiming Yang:
Hypertext Categorization using Hyperlink Patterns and Meta Data. ICML 2001: 178-185 - Mohammad Ghavamzadeh, Sridhar Mahadevan:
Continuous-Time Hierarchical Reinforcement Learning. ICML 2001: 186-193 - Matthew R. Glickman, Katia P. Sycara:
Evolutionary Search, Stochastic Policies with Memory, and Reinforcement Learning with Hidden State. ICML 2001: 194-201 - Greg Hamerly, Charles Elkan:
Bayesian approaches to failure prediction for disk drives. ICML 2001: 202-209 - Marcus Hutter:
General Loss Bounds for Universal Sequence Prediction. ICML 2001: 210-217 - Yuri A. Ivanov, Bruce Blumberg, Alex Pentland:
Expectation Maximization for Weakly Labeled Data. ICML 2001: 218-225 - Amir Jafari, Amy Greenwald, David Gondek, Gunes Ercal:
On No-Regret Learning, Fictitious Play, and Nash Equilibrium. ICML 2001: 226-233 - Wenxin Jiang:
Some Theoretical Aspects of Boosting in the Presence of Noisy Data. ICML 2001: 234-241 - Rong Jin, Alexander G. Hauptmann:
Learning to Select Good Title Words: An New Approach based on Reverse Information Retrieval. ICML 2001: 242-249 - Thorsten Joachims, Nello Cristianini, John Shawe-Taylor:
Composite Kernels for Hypertext Categorisation. ICML 2001: 250-257 - Stefan Kramer, Luc De Raedt:
Feature Construction with Version Spaces for Biochemical Applications. ICML 2001: 258-265 - Krzysztof Krawiec:
Pairwise Comparison of Hypotheses in Evolutionary Learning. ICML 2001: 266-273 - Abba Krieger, Chuan Long, Abraham J. Wyner:
Boosting Noisy Data. ICML 2001: 274-281 - John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira:
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML 2001: 282-289 - John Langford, Matthias W. Seeger, Nimrod Megiddo:
An Improved Predictive Accuracy Bound for Averaging Classifiers. ICML 2001: 290-297 - Patrice Latinne, Marco Saerens, Christine Decaestecker:
Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a multi-class problem in remote sensing. ICML 2001: 298-305 - Neil D. Lawrence, Bernhard Schölkopf:
Estimating a Kernel Fisher Discriminant in the Presence of Label Noise. ICML 2001: 306-313 - Wee Sun Lee:
Collaborative Learning and Recommender Systems. ICML 2001: 314-321 - Michael L. Littman:
Friend-or-Foe Q-learning in General-Sum Games. ICML 2001: 322-328 - Yufeng Liu, Rosemary Emery, Deepayan Chakrabarti, Wolfram Burgard, Sebastian Thrun:
Using EM to Learn 3D Models of Indoor Environments with Mobile Robots. ICML 2001: 329-336 - Xavier Llorà, Josep Maria Garrell i Guiu:
Inducing Partially-Defined Instances with Evolutionary Algorithms. ICML 2001: 337-344 - Mario Marchand, John Shawe-Taylor:
Learning with the Set Covering Machine. ICML 2001: 345-352 - Zvika Marx, Ido Dagan, Joachim M. Buhmann:
Coupled Clustering: a Method for Detecting Structural Correspondence. ICML 2001: 353-360 - Amy McGovern, Andrew G. Barto:
Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. ICML 2001: 361-368 - Prasanth B. Nair, Arindam Choudhury, Andy J. Keane:
Some Greedy Algorithms for Sparse Nonlinear Regression. ICML 2001: 369-376 - Andrew Y. Ng, Michael I. Jordan:
Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection. ICML 2001: 377-384 - Ilia Nouretdinov, Thomas Melluish, Volodya Vovk:
Ridge Regression Confidence Machine. ICML 2001: 385-392 - Athanassios Papagelis, Dimitrios Kalles:
Breeding Decision Trees Using Evolutionary Techniques. ICML 2001: 393-400 - Dan Pelleg, Andrew W. Moore:
Mixtures of Rectangles: Interpretable Soft Clustering. ICML 2001: 401-408 - Theodore J. Perkins, Andrew G. Barto:
Lyapunov-Constrained Action Sets for Reinforcement Learning. ICML 2001: 409-416 - Doina Precup, Richard S. Sutton, Sanjoy Dasgupta:
Off-Policy Temporal Difference Learning with Function Approximation. ICML 2001: 417-424 - Soumya Ray, David Page:
Multiple Instance Regression. ICML 2001: 425-432 - Marko Robnik-Sikonja, Igor Kononenko:
Comprehensible Interpretation of Relief's Estimates. ICML 2001: 433-440 - Nicholas Roy, Andrew McCallum:
Toward Optimal Active Learning through Sampling Estimation of Error Reduction. ICML 2001: 441-448 - Antonin Rozsypal, Miroslav Kubat:
Using the Genetic Algorithm to Reduce the Size of a Nearest-Neighbor Classifier and to Select Relevant Attributes. ICML 2001: 449-456 - Peter Sand, Andrew W. Moore:
Repairing Faulty Mixture Models using Density Estimation. ICML 2001: 457-464 - Manish Sarkar, Tze-Yun Leong:
Application of Fuzzy Similarity-Based Fractal Dimensions to Characterize Medical Time Series. ICML 2001: 465-472 - Makoto Sato, Shigenobu Kobayashi:
Average-Reward Reinforcement Learning for Variance Penalized Markov Decision Problems. ICML 2001: 473-480 - Tobias Scheffer, Stefan Wrobel:
Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems. ICML 2001: 481-488 - Mark Schwabacher, Pat Langley:
Discovering Communicable Scientific Knowledge from Spatio-Temporal Data. ICML 2001: 489-496 - Paola Sebastiani, Marco Ramoni:
Clustering Continuous Time Series. ICML 2001: 497-504 - Marc Sebban, Richard Nock, Stéphane Lallich:
Boosting Neighborhood-Based Classifiers. ICML 2001: 505-512 - Yevgeny Seldin, Gill Bejerano, Naftali Tishby:
Unsupervised Sequence Segmentation by a Mixture of Switching Variable Memory Markov Sources. ICML 2001: 513-520 - Gregory Shakhnarovich, Ran El-Yaniv, Yoram Baram:
Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation. ICML 2001: 521-528 - Bryan Singer, Manuela M. Veloso:
Learning to Generate Fast Signal Processing Implementations. ICML 2001: 529-536 - Peter Stone, Richard S. Sutton:
Scaling Reinforcement Learning toward RoboCup Soccer. ICML 2001: 537-544 - Malcolm J. A. Strens, Andrew W. Moore:
Direct Policy Search using Paired Statistical Tests. ICML 2001: 545-552 - Nigel Tao, Jonathan Baxter, Lex Weaver:
A Multi-Agent Policy-Gradient Approach to Network Routing. ICML 2001: 553-560 - Franck Thollard:
Improving Probabilistic Grammatical Inference Core Algorithms with Post-processing Techniques. ICML 2001: 561-568 - Anand Venkataraman:
A procedure for unsupervised lexicon learning. ICML 2001: 569-576 - Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan Schrödl:
Constrained K-means Clustering with Background Knowledge. ICML 2001: 577-584 - Marco A. Wiering:
Reinforcement Learning in Dynamic Environments using Instantiated Information. ICML 2001: 585-592 - Jeremy L. Wyatt:
Exploration Control in Reinforcement Learning using Optimistic Model Selection. ICML 2001: 593-600 - Eric P. Xing, Michael I. Jordan, Richard M. Karp:
Feature selection for high-dimensional genomic microarray data. ICML 2001: 601-608 - Bianca Zadrozny, Charles Elkan:
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. ICML 2001: 609-616 - Huajie Zhang, Charles X. Ling:
Learnability of Augmented Naive Bayes in Nonimal Domains. ICML 2001: 617-623 - Tong Zhang:
Some Sparse Approximation Bounds for Regression Problems. ICML 2001: 624-631 - Martin Zinkevich, Tucker R. Balch:
Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning. ICML 2001: 632-
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