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Semantic Scholar17. ICML 2000: Stanford, CA, USA
Pat Langley:
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29 - July 2, 2000. Morgan Kaufmann 2000, ISBN 1-55860-707-2- Ricardo Aler, Daniel Borrajo, Pedro Isasi:
Knowledge Representation Issues in Control Knowledge Learning. ICML 2000: 1-8 - Erin L. Allwein, Robert E. Schapire, Yoram Singer:
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. ICML 2000: 9-16 - Brigham S. Anderson, Andrew W. Moore, David Cohn:
A Nonparametric Approach to Noisy and Costly Optimization. ICML 2000: 17-24 - Charles W. Anderson, Bruce A. Draper, David A. Peterson:
Behavioral Cloning of Student Pilots with Modular Neural Networks. ICML 2000: 25-32 - Jonathan Baxter, Peter L. Bartlett:
Reinforcement Learning in POMDP's via Direct Gradient Ascent. ICML 2000: 41-48 - Kristin P. Bennett, Erin J. Bredensteiner:
Duality and Geometry in SVM Classifiers. ICML 2000: 57-64 - Kristin P. Bennett, Ayhan Demiriz, John Shawe-Taylor:
A Column Generation Algorithm For Boosting. ICML 2000: 65-72 - Mihai Boicu, Gheorghe Tecuci, Dorin Marcu, Michael Bowman, Ping Shyr, Florin Ciucu, Cristian Levcovici:
Disciple-COA: From Agent Programming to Agent Teaching. ICML 2000: 73-80 - Antony Francis Bowers, Christophe G. Giraud-Carrier, John W. Lloyd:
Classification of Individuals with Complex Structure. ICML 2000: 81-88 - Michael H. Bowling:
Convergence Problems of General-Sum Multiagent Reinforcement Learning. ICML 2000: 89-94 - Matthew Brand:
Finding Variational Structure in Data by Cross-Entropy Optimization. ICML 2000: 95-102 - Jake D. Brutlag, Christopher Meek:
Challenges of the Email Domain for Text Classification. ICML 2000: 103-110 - Colin Campbell, Nello Cristianini, Alexander J. Smola:
Query Learning with Large Margin Classifiers. ICML 2000: 111-118 - William M. Campbell, Kari Torkkola, Sreeream V. Balakrishnan:
Dimension Reduction Techniques for Training Polynomial Networks. ICML 2000: 119-126 - Huan Chang, David Cohn, Andrew McCallum:
Learning to Create Customized Authority Lists. ICML 2000: 127-134 - Eric Chown, Thomas G. Dietterich:
A Divide and Conquer Approach to Learning from Prior Knowledge. ICML 2000: 143-150 - Jefferson A. Coelho Jr., Roderic A. Grupen:
Learning in Non-stationary Conditions: A Control Theoretic Approach. ICML 2000: 151-158 - William W. Cohen:
Automatically Extracting Features for Concept Learning from the Web. ICML 2000: 159-166 - David Cohn, Huan Chang:
Learning to Probabilistically Identify Authoritative Documents. ICML 2000: 167-174 - Simon Colton, Alan Bundy, Toby Walsh:
Automatic Identification of Mathematical Concepts. ICML 2000: 183-190 - Jörg Conradt, Gaurav Tevatia, Sethu Vijayakumar, Stefan Schaal:
On-line Learning for Humanoid Robot Systems. ICML 2000: 191-198 - Mark Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner:
Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes. ICML 2000: 199-206 - Daniela Pucci de Farias, Benjamin Van Roy:
Fixed Points of Approximate Value Iteration and Temporal-Difference Learning. ICML 2000: 207-214 - Gerald DeJong:
Hidden Strengths and Limitations: An Empirical Investigation of Reinforcement Learning. ICML 2000: 215-222 - Pedro M. Domingos:
Bayesian Averaging of Classifiers and the Overfitting Problem. ICML 2000: 223-230 - Chris Drummond, Robert C. Holte:
Exploiting the Cost (In)sensitivity of Decision Tree Splitting Criteria. ICML 2000: 239-246 - Jennifer G. Dy, Carla E. Brodley:
Feature Subset Selection and Order Identification for Unsupervised Learning. ICML 2000: 247-254 - Eleazar Eskin:
Anomaly Detection over Noisy Data using Learned Probability Distributions. ICML 2000: 255-262 - Floriana Esposito, Nicola Fanizzi, Stefano Ferilli, Giovanni Semeraro:
Ideal Theory Refinement under Object Identity. ICML 2000: 263-270 - Theodoros Evgeniou, Luis Pérez-Breva, Massimiliano Pontil, Tomaso A. Poggio:
Bounds on the Generalization Performance of Kernel Machine Ensembles. ICML 2000: 271-278 - Claude-Nicolas Fiechter, Seth Rogers:
Learning Subjective Functions with Large Margins. ICML 2000: 287-294 - Jürgen Forster, Manfred K. Warmuth:
Relative Loss Bounds for Temporal-Difference Learning. ICML 2000: 295-302 - Attilio Giordana, Lorenza Saitta, Michèle Sebag, Marco Botta:
Analyzing Relational Learning in the Phase Transition Framework. ICML 2000: 311-318 - Dani Goldberg, Maja J. Mataric:
Learning Multiple Models for Reward Maximization. ICML 2000: 319-326 - Gregory Z. Grudic, Lyle H. Ungar:
Localizing Policy Gradient Estimates to Action Transition. ICML 2000: 343-350 - Keith B. Hall, Thomas Hofmann:
Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval. ICML 2000: 351-358 - Mark A. Hall:
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning. ICML 2000: 359-366 - Véronique Hoste, Walter Daelemans, Erik F. Tjong Kim Sang, Steven Gillis:
Meta-Learning for Phonemic Annotation of Corpora. ICML 2000: 375-382 - Dean F. Hougen, Maria L. Gini, James R. Slagle:
An Integrated Connectionist Approach to Reinforcement Learning for Robotic Control. ICML 2000: 383-390 - Chun-Nan Hsu, Hung-Ju Huang, Tzu-Tsung Wong:
Why Discretization Works for Naive Bayesian Classifiers. ICML 2000: 399-406 - Junling Hu, Michael P. Wellman:
Experimental Results on Q-Learning for General-Sum Stochastic Games. ICML 2000: 407-414 - Yi-Cheng Huang, Bart Selman, Henry A. Kautz:
Learning Declarative Control Rules for Constraint-BAsed Planning. ICML 2000: 415-422 - Fan Jiang, Michael L. Littman:
Approximate Dimension Equalization in Vector-based Information Retrieval. ICML 2000: 423-430 - Thorsten Joachims:
Estimating the Generalization Performance of an SVM Efficiently. ICML 2000: 431-438 - Peter Ju, Leslie Pack Kaelbling, Yoram Singer:
State-based Classification of Finger Gestures from Electromyographic Signals. ICML 2000: 439-446 - Susumu Katayama, Hajime Kimura, Shigenobu Kobayashi:
A Universal Generalization for Temporal-Difference Learning Using Haar Basis Functions. ICML 2000: 447-454 - Cenk Kaynak, Ethem Alpaydin:
MultiStage Cascading of Multiple Classifiers: One Man's Noise is Another Man's Data. ICML 2000: 455-462 - Jeffrey O. Kephart, Gerald Tesauro:
Pseudo-convergent Q-Learning by Competitive Pricebots. ICML 2000: 463-470 - Zu Whan Kim, Ramakant Nevatia:
Learning Bayesian Networks for Diverse and Varying numbers of Evidence Sets. ICML 2000: 479-486 - Ralf Klinkenberg, Thorsten Joachims:
Detecting Concept Drift with Support Vector Machines. ICML 2000: 487-494 - Paul Komarek, Andrew W. Moore:
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets. ICML 2000: 495-502 - Michail G. Lagoudakis, Michael L. Littman:
Algorithm Selection using Reinforcement Learning. ICML 2000: 511-518 - Terran Lane, Carla E. Brodley:
Data Reduction Techniques for Instance-Based Learning from Human/Computer Interface Data. ICML 2000: 519-526 - Tessa A. Lau, Pedro M. Domingos, Daniel S. Weld:
Version Space Algebra and its Application to Programming by Demonstration. ICML 2000: 527-534 - Martin Lauer, Martin A. Riedmiller:
An Algorithm for Distributed Reinforcement Learning in Cooperative Multi-Agent Systems. ICML 2000: 535-542 - Cen Li, Gautam Biswas:
A Bayesian Approach to Temporal Data Clustering using Hidden Markov Models. ICML 2000: 543-550 - Jinyan Li, Kotagiri Ramamohanarao, Guozhu Dong:
The Space of Jumping Emerging Patterns and Its Incremental Maintenance Algorithms. ICML 2000: 551-558 - Hiroshi Mamitsuka, Naoki Abe:
Efficient Mining from Large Databases by Query Learning. ICML 2000: 575-582 - Dragos D. Margineantu, Thomas G. Dietterich:
Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers. ICML 2000: 583-590 - Andrew McCallum, Dayne Freitag, Fernando C. N. Pereira:
Maximum Entropy Markov Models for Information Extraction and Segmentation. ICML 2000: 591-598 - Robert Moll, Theodore J. Perkins, Andrew G. Barto:
Machine Learning for Subproblem Selection. ICML 2000: 615-622 - Jun Morimoto, Kenji Doya:
Acquisition of Stand-up Behavior by a Real Robot using Hierarchical Reinforcement Learning. ICML 2000: 623-630 - Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan:
Learning Chomsky-like Grammars for Biological Sequence Families. ICML 2000: 631-638 - Matthew D. Mullin, Rahul Sukthankar:
Complete Cross-Validation for Nearest Neighbor Classifiers. ICML 2000: 639-646 - Rémi Munos, Andrew W. Moore:
Rates of Convergence for Variable Resolution Schemes in Optimal Control. ICML 2000: 647-654 - Kary Myers, Michael J. Kearns, Satinder P. Singh, Marilyn A. Walker:
A Boosting Approach to Topic Spotting on Subdialogues. ICML 2000: 655-662 - Daniel Nikovski, Illah R. Nourbakhsh:
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots. ICML 2000: 671-678 - Partha Niyogi, Narendra Karmarkar:
An Approach to Data Reduction and Clustering with Theoretical Guarantees. ICML 2000: 679-686 - Tadashi Nomoto, Yuji Matsumoto:
Comparing the Minimum Description Length Principle and Boosting in the Automatic Analysis of Discourse. ICML 2000: 687-694 - Seishi Okamoto, Nobuhiro Yugami:
Generalized Average-Case Analyses of the Nearest Neighbor Algorithm. ICML 2000: 695-702 - Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum:
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness. ICML 2000: 703-710 - Alberto Paccanaro, Geoffrey E. Hinton:
Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space. ICML 2000: 711-718 - Georgios Paliouras, Christos Papatheodorou, Vangelis Karkaletsis, Constantine D. Spyropoulos:
Clustering the Users of Large Web Sites into Communities. ICML 2000: 719-726 - Dan Pelleg, Andrew W. Moore:
X-means: Extending K-means with Efficient Estimation of the Number of Clusters. ICML 2000: 727-734 - David M. Pennock, Pedrito Maynard-Reid II, C. Lee Giles, Eric Horvitz:
A Normative Examination of Ensemble Learning Algorithms. ICML 2000: 735-742 - Bernhard Pfahringer, Hilan Bensusan, Christophe G. Giraud-Carrier:
Meta-Learning by Landmarking Various Learning Algorithms. ICML 2000: 743-750 - Justus H. Piater, Roderic A. Grupen:
Constructive Feature Learning and the Development of Visual Expertise. ICML 2000: 751-758 - Doina Precup, Richard S. Sutton, Satinder P. Singh:
Eligibility Traces for Off-Policy Policy Evaluation. ICML 2000: 759-766 - Jette Randløv:
Shaping in Reinforcement Learning by Changing the Physics of the Problem. ICML 2000: 767-774 - Jette Randløv, Andrew G. Barto, Michael T. Rosenstein:
Combining Reinforcement Learning with a Local Control Algorithm. ICML 2000: 775-782 - Stuart I. Reynolds:
Adaptive Resolution Model-Free Reinforcement Learning: Decision Boundary Partitioning. ICML 2000: 783-790 - Corinna Richter, Jörg Stachowiak:
Knowledge Propagation in Model-based Reinforcement Learning Tasks. ICML 2000: 791-798 - Malcolm R. K. Ryan, Mark D. Reid:
Learning to Fly: An Application of Hierarchical Reinforcement Learning. ICML 2000: 807-814 - Matthias Rychetsky, John Shawe-Taylor, Manfred Glesner:
Direct Bayes Point Machines. ICML 2000: 815-822 - Scott Sanner, John R. Anderson, Christian Lebiere, Marsha C. Lovett:
Achieving Efficient and Cognitively Plausible Learning in Backgammon. ICML 2000: 823-830 - Tobias Scheffer:
Predicting the Generalization Performance of Cross Validatory Model Selection Criteria. ICML 2000: 831-838 - Greg Schohn, David Cohn:
Less is More: Active Learning with Support Vector Machines. ICML 2000: 839-846 - Dale Schuurmans, Finnegan Southey:
An Adaptive Regularization Criterion for Supervised Learning. ICML 2000: 847-854 - Marc Sebban, Richard Nock:
Instance Pruning as an Information Preserving Problem. ICML 2000: 855-862 - Thomas R. Shultz, François Rivest:
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning. ICML 2000: 871-878 - Ricardo Bezerra de Andrade e Silva, Teresa Bernarda Ludermir:
Obtaining Simplified Rule Bases by Hybrid Learning. ICML 2000: 879-886 - Bryan Singer, Manuela M. Veloso:
Learning to Predict Performance from Formula Modeling and Training Data. ICML 2000: 887-894 - Seán Slattery, Tom M. Mitchell:
Discovering Test Set Regularities in Relational Domains. ICML 2000: 895-902 - William D. Smart, Leslie Pack Kaelbling:
Practical Reinforcement Learning in Continuous Spaces. ICML 2000: 903-910 - Alexander J. Smola, Bernhard Schölkopf:
Sparse Greedy Matrix Approximation for Machine Learning. ICML 2000: 911-918 - Leen-Kiat Soh, Costas Tsatsoulis:
Using Learning by Discovery to Segment Remotely Sensed Images. ICML 2000: 919-926 - Manu Sridharan, Gerald Tesauro:
Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions. ICML 2000: 927-934 - Luis Talavera:
Feature Selection and Incremental Learning of Probabilistic Concept Hierarchies. ICML 2000: 951-958 - Astro Teller, Manuela M. Veloso:
Efficient Learning Through Evolution: Neural Programming and Internal Reinforcement. ICML 2000: 959-966 - Loo-Nin Teow, Kia-Fock Loe:
Selection of Support Vector Kernel Parameters for Improved Generalization. ICML 2000: 967-974 - Franck Thollard, Pierre Dupont, Colin de la Higuera:
Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality. ICML 2000: 975-982 - Ljupco Todorovski, Saso Dzeroski, Ashwin Srinivasan, Jonathan P. Whiteley, David Gavaghan:
Discovering the Structure of Partial Differential Equations from Example Behaviour. ICML 2000: 991-998 - Simon Tong, Daphne Koller:
Support Vector Machine Active Learning with Application sto Text Classification. ICML 2000: 999-1006 - Kari Torkkola, William M. Campbell:
Mutual Information in Learning Feature Transformations. ICML 2000: 1015-1022 - Geoffrey G. Towell, Thomas Petsche, Michael R. Miller:
Learning Priorities From Noisy Examples. ICML 2000: 1031-1038 - Tim Van Allen, Russell Greiner:
Model Selection Criteria for Learning Belief Nets: An Empirical Comparison. ICML 2000: 1047-1054 - Antal van den Bosch, Jakub Zavrel:
Unpacking Multi-valued Symbolic Features and Classes in Memory-Based Language Learning. ICML 2000: 1055-1062 - Menno van Zaanen:
Bootstrapping Syntax and Recursion using Alginment-Based Learning. ICML 2000: 1063-1070 - Stefan Veeser:
An Evolutionary Approach to Evidence-Based Learning of Deterministic Finite Automata. ICML 2000: 1071-1078 - Sethu Vijayakumar, Stefan Schaal:
Locally Weighted Projection Regression: Incremental Real Time Learning in High Dimensional Space. ICML 2000: 1079-1086 - Ricardo Vilalta, Daniel Oblinger:
A Quantification of Distance Bias Between Evaluation Metrics In Classification. ICML 2000: 1087-1094 - Slobodan Vucetic, Zoran Obradovic:
Discovering Homogeneous Regions in Spatial Data through Competition. ICML 2000: 1095-1102