15. ICML 1998: Madison, Wisconsin, USA
Jude W. Shavlik (Ed.): Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998. Morgan Kaufmann 1998 ISBN 1-55860-556-8- Ricardo Aler, Daniel Borrajo, Pedro Isasi: Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach. 10-18
- Cosimo Anglano, Attilio Giordana, Giuseppe Lo Bello, Lorenza Saitta: An Experimental Evaluation of Coevolutive Concept Learning. 19-27
- Jonathan Baxter, Andrew Tridgell, Lex Weaver: KnightCap: A Chess Programm That Learns by Combining TD(lambda) with Game-Tree Search. 28-36
- Stephen D. Bay: Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets. 37-45
- Kurt D. Bollacker, Joydeep Ghosh: A Supra-Classifier Architecture for Scalable Knowledge Reuse. 64-72
- Paul S. Bradley, Olvi L. Mangasarian: Feature Selection via Concave Minimization and Support Vector Machines. 82-90
- Nicolò Cesa-Bianchi, Paul Fischer: Finite-Time Regret Bounds for the Multiarmed Bandit Problem. 100-108
- Nello Cristianini, John Shawe-Taylor, Peter Sykacek: Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space. 109-117
- Thomas G. Dietterich: The MAXQ Method for Hierarchical Reinforcement Learning. 118-126
- Pedro Domingos: A Process-Oriented Heuristic for Model Selection. 127-135
- Eibe Frank, Ian H. Witten: Using a Permutation Test for Attribute Selection in Decision Trees. 152-160
- Dayne Freitag: Multistrategy Learning for Information Extraction. 161-169
- Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer: An Efficient Boosting Algorithm for Combining Preferences. 170-178
- Nir Friedman, Moisés Goldszmidt, Thomas J. Lee: Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting. 179-187
- Thilo-Thomas Frieß, Nello Cristianini, Colin Campbell: The Kernel-Adatron Algorithm: A Fast and Simple Learning Procedure for Support Vector Machines. 188-196
- Joao Gama: Local Cascade Generalization. 206-214
- Frédérick Garcia, Seydina M. Ndiaye: A Learning Rate Analysis of Reinforcement Learning Algorithms in Finite-Horizon. 215-223
- Diana F. Gordon: Well-Behaved Borgs, Bolos, and Berserkers. 224-232
- Tom Heskes: Solving a Huge Number of Similar Tasks: A Combination of Multi-Task Learning and a Hierarchical Bayesian Approach. 233-241
- Junling Hu, Michael P. Wellman: Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm. 242-250
- Michael J. Kearns, Satinder P. Singh: Near-Optimal Reinforcement Learning in Polynominal Time. 260-268
- Michael J. Kearns, Yishay Mansour: A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization. 269-277
- Hajime Kimura, Shigenobu Kobayashi: An Analysis of Actor/Critic Algorithms Using Eligibility Traces: Reinforcement Learning with Imperfect Value Function. 278-286
- Dekang Lin: An Information-Theoretic Definition of Similarity. 296-304
- Michel Liquiere, Jean Sallantin: Structural Machine Learning with Galois Lattice and Graphs. 305-313
- Michael L. Littman, Fan Jiang, Greg A. Keim: Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus. 314-322
- John Loch, Satinder P. Singh: Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes. 323-331
- Dimitris Margaritis, Sebastian Thrun: Learning to Locate an Object in 3D Space from a Sequence of Camera Images. 332-340
- Oded Maron, Aparna Lakshmi Ratan: Multiple-Instance Learning for Natural Scene Classification. 341-349
- Andrew McCallum, Kamal Nigam: Employing EM and Pool-Based Active Learning for Text Classification. 350-358
- Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng: Improving Text Classification by Shrinkage in a Hierarchy of Classes. 359-367
- T. L. McCluskey, Margaret Mary West: A Case Study in the Use of Theory Revision in Requirements Validation. 368-376
- Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, Mary S. Lee: Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. 386-394
- Atsuyoshi Nakamura, Naoki Abe: Collaborative Filtering Using Weighted Majority Prediction Algorithms. 395-403
- Andrew Y. Ng: On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples. 404-412
- Mark D. Pendrith, Michael McGarity: An Analysis of Direct Reinforcement Learning in Non-Markovian Domains. 421-429
- Justus H. Piater, Paul R. Cohen, Xiaoqin Zhang, Michael Atighetchi: A Randomized ANOVA Procedure for Comparing Performance Curves. 430-438
- Doina Precup, Paul E. Utgoff: Classification Using Phi-Machines and Constructive Function Approximation. 439-444
- Foster J. Provost, Tom Fawcett, Ron Kohavi: The Case against Accuracy Estimation for Comparing Induction Algorithms. 445-453
- Sowmya Ramachandran, Raymond J. Mooney: Theory Refinement of Bayesian Networks with Hidden Variables. 454-462
- Jette Randløv, Preben Alstrøm: Learning to Drive a Bicycle Using Reinforcement Learning and Shaping. 463-471
- Chandra Reddy, Prasad Tadepalli: Learning First-Order Acyclic Horn Programs from Entailment. 472-480
- Malcolm R. K. Ryan, Mark D. Pendrith: RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning. 481-487
- Rafal Salustowicz, Jürgen Schmidhuber: Evolving Structured Programs with Hierarchical Instructions and Skip Nodes. 488-496
- Ken Samuel, Sandra Carberry, K. Vijay-Shanker: An Investigation of Transformation-Based Learning in Discourse. 497-505
- Lawrence K. Saul: Automatic Segmentation of Continuous Trajectories with Invariance to Nonlinear Warpings of Time. 506-514
- Craig Saunders, Alexander Gammerman, Volodya Vovk: Ridge Regression Learning Algorithm in Dual Variables. 515-521
- Jeff G. Schneider, Justin A. Boyan, Andrew W. Moore: Value Function Based Production Scheduling. 522-530
- W. Nick Street: A Neural Network Model for Prognostic Prediction. 540-546
- Richard S. Sutton, Doina Precup, Satinder P. Singh: Intra-Option Learning about Temporally Abstract Actions. 556-564
data released under the ODC-BY 1.0 license. See also our legal information page
last updated on 2013-06-19T203413 by the dblp team