Abstract is missing.
- Challenges in Machine Learning for Text ClassificationDavid D. Lewis. 1 [doi]
- VC Dimension of an Integrate-and-Fire Neuron ModelAnthony M. Zador, Barak A. Pearlmutter. 10-18 [doi]
- Graph Learning with a Nearest Neighbor ApproachSven Koenig, Yury V. Smirnov. 19-28 [doi]
- The Dual DFA Learning Problem: Hardness Results for Programming by Demonstration and Learning First-Order Representations (Extended Abstract)William W. Cohen. 29-40 [doi]
- PAC-Like Upper Bounds for the Sample Complexity of Leave-one-Out Cross-ValidationSean B. Holden. 41-50 [doi]
- A Data-Dependent Skeleton Estimate for LearningGábor Lugosi, Márta Pintér. 51-56 [doi]
- Towards Robust Model Selection Using Estimation and Approximation Error BoundsJoel Ratsaby, Ron Meir, Vitaly Maiorov. 57-67 [doi]
- A Framework for Structural Risk MinimisationJohn Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, Martin Anthony. 68-76 [doi]
- A Bayesian/Information Theoretic Model of Bias LearningJonathan Baxter. 77-88 [doi]
- Predicting a Binary Sequence Almost As Well As the Optimal Biased CoinYoav Freund. 89-98 [doi]
- A Randomized Approximation of the MDL for Stochastic Models with Hidden VariablesKenji Yamanishi. 99-109 [doi]
- On the Complexity of Learning from Drifting DistributionsRakesh D. Barve, Philip M. Long. 122-130 [doi]
- Learning Changing Concepts by Exploiting the Structure of ChangePeter L. Bartlett, Shai Ben-David, Sanjeev R. Kulkarni. 131-139 [doi]
- The Importance of Convexity in Learning with Squared LossWee Sun Lee, Peter L. Bartlett, Robert C. Williamson. 140-146 [doi]
- Learning Curve Bounds for a Markov Decision Process with Undiscounted RewardsLawrence K. Saul, Satinder P. Singh. 147-156 [doi]
- Probabilistic and Team PFIN-Type Learning: General PropertiesAndris Ambainis. 157-168 [doi]
- Synthesizing Enumeration Techniques for Language LearningGanesh Baliga, John Case, Sanjay Jain. 169-180 [doi]
- Elementary Formal Systems, Intrinsic Complexity, and ProcrastinationSanjay Jain, Arun Sharma. 181-192 [doi]
- Angluin s Theorem for Indexed Families of r.e. Sets and ApplicationsDick De Jongh, Makoto Kanazawa. 193-204 [doi]
- On Restricted-Focus-of-Attention Learnability of Boolean FunctionsAndreas Birkendorf, Eli Dichterman, Jeffrey C. Jackson, Norbert Klasner, Hans-Ulrich Simon. 205-216 [doi]
- On Learning width Two Branching Programs (Extended Abstract)Nader H. Bshouty, Christino Tamon, David K. Wilson. 224-227 [doi]
- PAC Learning Axis-Aligned Rectangles with Respect to Product Distributions from Multiple-Instance ExamplesPhilip M. Long, Lei Tan. 228-234 [doi]
- Attribute-Efficient Learning in Query and Mistake-Bound ModelsNader H. Bshouty, Lisa Hellerstein. 235-243 [doi]
- PAC Learning Intersections of Halfspaces with Membership Queries (Extended Abstract)Stephen Kwek, Leonard Pitt. 244-254 [doi]
- Learning Conjunctions of Two Unate DNF Formulas (Extended Abstract): Computational and Informational ResultsAaron Feigelson, Lisa Hellerstein. 255-265 [doi]
- A Simple Algorithm for Learning O(log n)-Term DNFEyal Kushilevitz. 266-269 [doi]
- Trees and LearningWolfgang Merkle, Frank Stephan. 270-279 [doi]
- Learning Branches and Learning to Win Closed GamesMartin Kummer, Matthias Ott. 280-291 [doi]
- A Competitive Approach to Game LearningChristopher D. Rosin, Richard K. Belew. 292-302 [doi]
- Strong Minimax Lower Bounds for LearningAndrás Antos, Gábor Lugosi. 303-309 [doi]
- On-Line Portfolio SelectionErik Ordentlich, Thomas M. Cover. 310-313 [doi]
- On Bayes Methods for On-Line Boolean PredictionNicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza. 314-324 [doi]
- Game Theory, On-Line Prediction and BoostingYoav Freund, Robert E. Schapire. 325-332 [doi]
- Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract)Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth. 333-343 [doi]