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15th COLT 2002: Sydney, Australia
- Jyrki Kivinen, Robert H. Sloan:
Computational Learning Theory, 15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 8-10, 2002, Proceedings. Lecture Notes in Computer Science 2375, Springer 2002, ISBN 3-540-43836-X - Shahar Mendelson, Robert C. Williamson:
Agnostic Learning Nonconvex Function Classes. 1-13 - Shahar Mendelson, Roman Vershynin:
Entropy, Combinatorial Dimensions and Random Averages. 14-28 - Shahar Mendelson:
Geometric Parameters of Kernel Machines. 29-43 - Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson:
Localized Rademacher Complexities. 44-58 - Olivier Bousquet, Vladimir Koltchinskii, Dmitriy Panchenko:
Some Local Measures of Complexity of Convex Hulls and Generalization Bounds. 59-73 - Eiji Takimoto, Manfred K. Warmuth:
Path Kernels and Multiplicative Updates. 74-89 - Michael V. Vyugin, Vladimir V. V'yugin:
Predictive Complexity and Information. 90-104 - Yuri Kalnishkan, Michael V. Vyugin:
Mixability and the Existence of Weak Complexities. 105-120 - Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile:
A Second-Order Perceptron Algorithm. 121-137 - Chris Mesterharm:
Tracking Linear-Threshold Concepts with Winnow. 138-152 - Henning Fernau
:
Learning Tree Languages from Text. 153-168 - Yusuke Suzuki, Ryuta Akanuma, Takayoshi Shoudai, Tetsuhiro Miyahara, Tomoyuki Uchida:
Polynomial Time Inductive Inference of Ordered Tree Patterns with Internal Structured Variables from Positive Data. 169-184 - Colin de la Higuera, José Oncina
:
Inferring Deterministic Linear Languages. 185-200 - Sandra Zilles:
Merging Uniform Inductive Learners. 201-215 - Jürgen Schmidhuber:
The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions. 216-228 - Ke Yang:
New Lower Bounds for Statistical Query Learning. 229-243 - Nader H. Bshouty, Jeffrey C. Jackson, Christino Tamon:
Exploring Learnability between Exact and PAC. 244-254 - Eyal Even-Dar, Shie Mannor
, Yishay Mansour:
PAC Bounds for Multi-armed Bandit and Markov Decision Processes. 255-270 - Nader H. Bshouty, Lynn Burroughs:
Bounds for the Minimum Disagreement Problem with Applications to Learning Theory. 271-286 - Nader H. Bshouty, Lynn Burroughs:
On the Proper Learning of Axis Parallel Concepts. 287-302 - Gábor Lugosi, Nicolas Vayatis:
A Consistent Strategy for Boosting Algorithms. 303-318 - Shie Mannor
, Ron Meir, Tong Zhang:
The Consistency of Greedy Algorithms for Classification. 319-333 - Gunnar Rätsch
, Manfred K. Warmuth:
Maximizing the Margin with Boosting. 334-350 - Sanjoy Dasgupta:
Performance Guarantees for Hierarchical Clustering. 351-363 - Marcus Hutter
:
Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures. 364-379 - Lance Fortnow, Jack H. Lutz:
Prediction and Dimension. 380-395 - Christos H. Papadimitriou:
Learning the Internet. 396
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