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ORCID16th ICML 1999: Bled, Slovenia
- Ivan Bratko, Saso Dzeroski:
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999. Morgan Kaufmann 1999, ISBN 1-55860-612-2 - Naoki Abe, Philip M. Long:
Associative Reinforcement Learning using Linear Probabilistic Concepts. ICML 1999: 3-11 - Naoki Abe, Atsuyoshi Nakamura:
Learning to Optimally Schedule Internet Banner Advertisements. ICML 1999: 12-21 - Enrico Blanzieri, Francesco Ricci:
A Minimum Risk Metric for Nearest Neighbor Classification. ICML 1999: 22-31 - Gianluca Bontempi, Mauro Birattari, Hugues Bersini:
Local Learning for Iterated Time-Series Prediction. ICML 1999: 32-38 - Antal van den Bosch:
Instance-Family Abstraction in Memory-Based Language Learning. ICML 1999: 39-48 - Justin A. Boyan:
Least-Squares Temporal Difference Learning. ICML 1999: 49-56 - Mark Brodie, Gerald DeJong:
Learning to Ride a Bicycle using Iterated Phantom Induction. ICML 1999: 57-66 - Wolfram Burgard, Dieter Fox, Hauke Jans, Christian Matenar, Sebastian Thrun:
Sonar-Based Mapping of Large-Scale Mobile Robot Environments using EM. ICML 1999: 67-76 - Igor V. Cadez, Christine E. McLaren, Padhraic Smyth, Geoffrey J. McLachlan:
Hierarchical Models for Screening of Iron Deficiency Anemia. ICML 1999: 77-86 - Claire Cardie, Scott Anthony Mardis, David R. Pierce:
Combining Error-Driven Pruning and Classification for Partial Parsing. ICML 1999: 87-96 - Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip K. Chan:
AdaCost: Misclassification Cost-Sensitive Boosting. ICML 1999: 97-105 - Laura Firoiu, Paul R. Cohen:
Abstracting from Robot Sensor Data using Hidden Markov Models. ICML 1999: 106-114 - Eibe Frank, Ian H. Witten:
Making Better Use of Global Discretization. ICML 1999: 115-123 - Yoav Freund, Llew Mason:
The Alternating Decision Tree Learning Algorithm. ICML 1999: 124-133 - João Gama:
Discriminant Trees. ICML 1999: 134-142 - Dragan Gamberger, Nada Lavrac, Ciril Groselj:
Experiments with Noise Filtering in a Medical Domain. ICML 1999: 143-151 - Melinda T. Gervasio, Wayne Iba, Pat Langley:
Learning User Evaluation Functions for Adaptive Scheduling Assistance. ICML 1999: 152-161 - Attilio Giordana, Roberto Piola:
On Some Misbehaviour of Back-Propagation with Non-Normalized RBFNs and a Solution. ICML 1999: 162-170 - Michael Bonnell Harries:
Boosting a Strong Learner: Evidence Against the Minimum Margin. ICML 1999: 171-180 - Yuh-Jyh Hu, Suzanne B. Sandmeyer, Dennis F. Kibler:
Detecting Motifs from Sequences. ICML 1999: 181-190 - Daisuke Iijima, Wenwei Yu, Hiroshi Yokoi, Yukinori Kakazu:
Distributed Robotic Learning: Adaptive Behavior Acquisition for Distributed Autonomous Swimming Robot in Real World. ICML 1999: 191-199 - Thorsten Joachims:
Transductive Inference for Text Classification using Support Vector Machines. ICML 1999: 200-209 - Hajime Kimura, Shigenobu Kobayashi:
Efficient Non-Linear Control by Combining Q-learning with Local Linear Controllers. ICML 1999: 210-219 - Pat Langley, Stephanie Sage:
Tractable Average-Case Analysis of Naive Bayesian Classifiers. ICML 1999: 220-228 - Michael van Lent, John E. Laird:
Learning Hierarchical Performance Knowledge by Observation. ICML 1999: 229-238 - Choh Man Teng:
Correcting Noisy Data. ICML 1999: 239-248 - Marina Meila:
An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High-Dimensional Sparse Data. ICML 1999: 249-257 - Dunja Mladenic, Marko Grobelnik:
Feature Selection for Unbalanced Class Distribution and Naive Bayes. ICML 1999: 258-267 - Katharina Morik, Peter Brockhausen, Thorsten Joachims:
Combining Statistical Learning with a Knowledge-Based Approach - A Case Study in Intensive Care Monitoring. ICML 1999: 268-277 - Andrew Y. Ng, Daishi Harada, Stuart Russell:
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. ICML 1999: 278-287 - Maziar Palhang, Arcot Sowmya:
Learning Discriminatory and Descriptive Rules by an Inductive Logic Programming System. ICML 1999: 288-297 - Rajesh Parekh, Vasant G. Honavar:
Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples. ICML 1999: 298-306 - Leonid Peshkin, Nicolas Meuleau, Leslie Pack Kaelbling:
Learning Policies with External Memory. ICML 1999: 307-314 - Uros Pompe:
Noise-Tolerant Recursive Best-First Induction. ICML 1999: 315-324 - Bob Price, Craig Boutilier:
Implicit Imitation in Multiagent Reinforcement Learning. ICML 1999: 325-334 - Jason Rennie, Andrew Kachites McCallum:
Using Reinforcement Learning to Spider the Web Efficiently. ICML 1999: 335-343 - Marko Robnik-Sikonja, Igor Kononenko:
Attribute Dependencies, Understandability and Split Selection in Tree Based Models. ICML 1999: 344-353 - Yasubumi Sakakibara, Mitsuhiro Kondo:
GA-based Learning of Context-Free Grammars using Tabular Representations. ICML 1999: 354-360 - Tobias Scheffer, Thorsten Joachims:
Expected Error Analysis for Model Selection. ICML 1999: 361-370 - Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller:
Distributed Value Functions. ICML 1999: 371-378 - Sam Scott, Stan Matwin:
Feature Engineering for Text Classification. ICML 1999: 379-388 - Luis Talavera:
Feature Selection as a Preprocessing Step for Hierarchical Clustering. ICML 1999: 389-397 - Douglas A. Talbert, Douglas H. Fisher:
OPT-KD: An Algorithm for Optimizing Kd-Trees. ICML 1999: 398-405 - Cynthia A. Thompson, Mary Elaine Califf, Raymond J. Mooney:
Active Learning for Natural Language Parsing and Information Extraction. ICML 1999: 406-414 - Sebastian Thrun, John Langford, Dieter Fox:
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes. ICML 1999: 415-424 - Paul E. Utgoff, David J. Stracuzzi:
Approximation Via Value Unification. ICML 1999: 425-432 - Shivakumar Vaithyanathan, Byron Dom:
Model Selection in Unsupervised Learning with Applications To Document Clustering. ICML 1999: 433-443 - Volodya Vovk, Alexander Gammerman, Craig Saunders:
Machine-Learning Applications of Algorithmic Randomness. ICML 1999: 444-453 - Mohammed Waleed Kadous:
Learning Comprehensible Descriptions of Multivariate Time Series. ICML 1999: 454-463 - Gang Wang, Sridhar Mahadevan:
Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes. ICML 1999: 464-473 - Donghui Wu, Kristin P. Bennett, Nello Cristianini, John Shawe-Taylor:
Large Margin Trees for Induction and Transduction. ICML 1999: 474-483 - Wei Zhang:
An Region-Based Learning Approach to Discovering Temporal Structures in Data. ICML 1999: 484-492 - Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting:
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees. ICML 1999: 493-502 - Yuanhui Zhou, Carla E. Brodley:
A Hybrid Lazy-Eager Approach to Reducing the Computation and Memory Requirements of Local Parametric Learning Algorithms. ICML 1999: 503-
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