Abstract is missing.
- Learning Word Association Norms Using Tree Cut Pair ModelsNaoki Abe, Hang Li. 3-11
- K Nearest Neighbor Classification on Feature ProjectionsAynur Akkus, H. Altay Güvenir. 12-19
- Toward a Model of Mind as a Laissez-Faire Economy of IdiotsEric B. Baum. 28-36
- Theory-Guideed Induction of Logic Programs by Inference of Regular LanguagesHenrik Boström. 46-53
- Approximate Value Trees in Structured Dynamic ProgrammingCraig Boutilier, Richard Dearden. 54-62
- Learning Evaluation Functions for Large Acyclic DomainsJustin A. Boyan, Andrew W. Moore. 63-70
- Simplified Support Vector Decision RulesChristopher J. C. Burges. 71-77
- Improving the Efficiency of Knowledge Base RefinementLeonardo Carbonara, Derek H. Sleeman. 78-86
- Algorithms and Applications for Multitask LearningRich Caruana. 87-95
- Applying the Waek Learning Framework to Understand and Improve C4.5Thomas G. Dietterich, Michael J. Kearns, Yishay Mansour. 96-104
- Beyond Independence: Conditions for the Optimality of the Simple Bayesian ClassifierPedro Domingos, Michael J. Pazzani. 105-112
- Relational Instance-Based LearningWerner Emde, Dietrich Wettschereck. 122-130
- Identifying the Information Contained in a Flawed TheorySean P. Engelson, Moshe Koppel. 131-138
- Learning Goal Oriented Bayesian Networks for Telecommunications Risk ManagementKazuo J. Ezawa, Moninder Singh, Steven W. Norton. 139-147
- Experiments with a New Boosting AlgorithmYoav Freund, Robert E. Schapire. 148-156
- Discretizing Continuous Attributes While Learning Bayesian NetworksNir Friedman, Moisés Goldszmidt. 157-165
- Learning Relational Concepts with Decision TreesPeter Geibel, Fritz Wysotzki. 166-174
- On-Line Adaptation of a Signal Predistorter through Dual Reinforcement LearningPatrick Goetz, Shailesh Kumar, Risto Miikkulainen. 175-181
- Applying Winnow to Context-Sensitive Spelling CorrectionAndrew R. Golding, Dan Roth. 182-190
- Nonparametric Statistical Methods for Experimental Evaluations of Speedup LearningGeoffrey J. Gordon, Alberto Maria Segre. 200-206
- Learning Active ClassifiersRussell Greiner, Adam J. Grove, Dan Roth. 207-215
- Exploiting the Omission of Irrelevant DataRussell Greiner, Adam J. Grove, Alexander Kogan. 216-224
- Speeding-up Nearest Neighbour Memories: The Template Tree Case Memory OrganisationStephan Grolimund, Jean-Gabriel Ganascia. 225-233
- On-Line Portfolio Selection Using Multiplicative UpdatesDavid P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth. 243-251
- Non-Linear Decision Trees - NDTAndreas Ittner, Michael Schlosser. 252-257
- Negative Robust Learning Results from Horn Claus ProgramsPascal Jappy, Richard Nock, Olivier Gascuel. 258-265
- Passive Distance Learning for Robot NavigationSven Koenig, Reid G. Simmons. 266-274
- Bias Plus Variance Decomposition for Zero-One Loss FunctionsRon Kohavi, David Wolpert. 275-283
- Toward Optimal Feature SelectionDaphne Koller, Mehran Sahami. 284-292
- Second Tier for Decision TreesMiroslav Kubat. 293-301
- On the Learnability of the UncomputableRichard H. Lathrop. 302-309
- A Generalized Reinforcement-Learning Model: Convergence and ApplicationsMichael L. Littman, Csaba Szepesvári. 310-318
- Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement LearningSridhar Mahadevan. 328-336
- A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement LearningRémi Munos. 337-345
- Searching for Structure in Multiple Streams of DataTim Oates, Paul R. Cohen. 346-354
- Theoretical Analysis of the Nearest Neighbor Classifier in Noisy DomainsSeishi Okamoto, Nobuhiro Yugami. 355-363
- Unsupervised Learning Using MMLJonathan J. Oliver, Rohan A. Baxter, Chris S. Wallace. 364-372
- Actual Return Reinforcement Learning versus Temporal Differences: Some Theoretical and Experimental ResultsMark D. Pendrith, Malcolm R. K. Ryan. 373-381
- Representing and Learning Quality-Improving Search Control KnowledgeM. Alicia Pérez. 382-390
- Learning Despite Concept Variation by Finding Structure in Attribute-based DataEduardo Pérez, Larry A. Rendell. 391-399
- An Advanced Evolution Should Not Repeat its Past ErrorsCaroline Ravise, Michèle Sebag. 400-408
- Theory-guided Empirical Speedup Learning of Goal Decomposition RulesChandra Reddy, Prasad Tadepalli, Silvana Roncagliolo. 409-417
- Analogy Access by Mapping Spreading and Abstraction in Large, Multifunctional Knowledge BasesDavide Roverso. 418-426
- Non Mean Square Error Criteria for the Training of Learning MachinesMarco Saerens. 427-434
- Efficient Learning of Selective Bayesian Network ClassifiersMoninder Singh, Gregory M. Provan. 453-461
- Learning Bayesian Belief Networks Based on the Minimum Description Length Principle: An Efficient Algorithm Using the B & B TechniqueJoe Suzuki. 462-470
- Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value FunctionPrasad Tadepalli, DoKyeong Ok. 471-479
- Experimental Knowledge Acquisition for PlanningKang Soo Tae, Diane J. Cook. 480-488
- Discovering Structure in Multiple Learning Tasks: The TC AlgorithmSebastian Thrun, Joseph O Sullivan. 489-497
- Prababilistic Instance-Based LearningHenry Tirri, Petri Kontkanen, Petri Myllymäki. 507-515
- Causal Discovery via MMLChris S. Wallace, Kevin B. Korb, Honghua Dai. 516-524
- Recognition and Exploitation of Contextual CLues via Incremental Meta-LearningGerhard Widmer. 525-533
- Solving POMDPs with Levin Search and EIRAMarco Wiering, Jürgen Schmidhuber. 534-542
- Representation Changes for Efficient Learning in Structural DomainsJean-Daniel Zucker, Jean-Gabriel Ganascia. 543-551
- Data Mining and Machine Learning (Abstract)Heikki Mannila. 555
- Reinforcement Learning in Factories: The Auton Project (Abstract)Andrew W. Moore. 556
- Statistical Theory of Generalization (Abstract)Vladimir Vapnik. 557