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