Abstract is missing.
- Minimax Regret Under log Loss for General Classes of ExpertsNicolò Cesa-Bianchi, Gábor Lugosi. 12-18 [doi]
- Regret Bounds for Prediction ProblemsGeoffrey J. Gordon. 29-40 [doi]
- On Theory Revision with QueriesRobert H. Sloan, György Turán. 41-52 [doi]
- Estimating a Mixture of Two Product DistributionsYoav Freund, Yishay Mansour. 53-62 [doi]
- An Apprentice Learning Model (extended abstract)Stephen Kwek. 63-74 [doi]
- Uniform-Distribution Attribute Noise LearnabilityNader H. Bshouty, Jeffrey C. Jackson, Christino Tamon. 75-80 [doi]
- On Learning in the Presence of Unspecified Attribute ValuesNader H. Bshouty, David K. Wilson. 81-87 [doi]
- Learning Fixed-Dimension Linear Thresholds from Fragmented DataPaul W. Goldberg. 88-99 [doi]
- Approximation Algorithms for Clustering ProblemsDavid B. Shmoys. 100-102 [doi]
- An Adaptive Version of the Boost by Majority AlgorithmYoav Freund. 102-113 [doi]
- Drifting GamesRobert E. Schapire. 114-124 [doi]
- Additive Models, Boosting, and Inference for Generalized DivergencesJohn D. Lafferty. 125-133 [doi]
- Boosting as Entropy ProjectionJyrki Kivinen, Manfred K. Warmuth. 134-144 [doi]
- Multiclass Learning, Boosting, and Error-Correcting CodesVenkatesan Guruswami, Amit Sahai. 145-155 [doi]
- Theoretical Analysis of a Class of Randomized Regularization MethodsTong Zhang. 156-163 [doi]
- PAC-Bayesian Model AveragingDavid A. McAllester. 164-170 [doi]
- Viewing all Models as Probabilistic Peter Grünwald. 171-182 [doi]
- Reinforcement Learning and Mistake Bounded AlgorithmsYishay Mansour. 183-192 [doi]
- Convergence Analysis of Temporal-Difference Learning Algorithms with Linear Function ApproximationVladislav Tadic. 193-202 [doi]
- Beating the Hold-Out: Bounds for K-fold and Progressive Cross-ValidationAvrim Blum, Adam Kalai, John Langford. 203-208 [doi]
- Microchoice Bounds and Self Bounding Learning AlgorithmsJohn Langford, Avrim Blum. 209-214 [doi]
- Learning Specialist Decision ListsAtsuyoshi Nakamura. 215-225 [doi]
- Linear Relations between Square-Loss and Kolmogorov ComplexityYuri Kalnishkan. 226-232 [doi]
- Individual Sequence Prediction - Upper Bounds and Application for ComplexityChamy Allenberg. 233-242 [doi]
- Extensional Set Learning (extended abstract)Sebastiaan Terwijn. 243-248 [doi]
- On a Generalized Notion of Mistake BoundsSanjay Jain, Arun Sharma. 249-256 [doi]
- On the Intrinsic Complexity of Learning Recursive FunctionsEfim B. Kinber, Christophe Papazian, Carl H. Smith, Rolf Wiehagen. 257-266 [doi]
- Covering Numbers for Support Vector MachinesYing Guo, Peter L. Bartlett, John Shawe-Taylor, Robert C. Williamson. 267-277 [doi]
- Further Results on the Margin DistributionJohn Shawe-Taylor, Nello Cristianini. 278-285 [doi]
- More Efficient PAC-Learning of DNF with Membership Queries Under the Uniform DistributionNader H. Bshouty, Jeffrey C. Jackson, Christino Tamon. 286-295 [doi]
- Learning Threshold Functions with Small Weights Using Membership QueriesElias Abboud, Nader Agha, Nader H. Bshouty, Nizar Radwan, Fathi Saleh. 318-322 [doi]
- Exact Learning of Unordered Tree Patterns from QueriesThomas R. Amoth, Paul Cull, Prasad Tadepalli. 323-332 [doi]