16. COLT 2003: Washington, DC, USA
Bernhard Schölkopf, Manfred K. Warmuth (Eds.): Computational Learning Theory and Kernel Machines, 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings. Springer 2003 Lecture Notes in Computer Science ISBN 3-540-40720-0
Target Area: Computational Game Theory
- Michael L. Littman: Tutorial: Learning Topics in Game-Theoretic Decision Making. 1
Invited Talk
- Amy Greenwald, Amir Jafari: A General Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria. 2-12
Contributed Talks
- Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, Martin Zinkevich: Preference Elicitation and Query Learning. 13-25
Kernel Machines
- Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik: Knowledge-Based Nonlinear Kernel Classifiers. 102-113
- Thomas Gärtner, Peter A. Flach, Stefan Wrobel: On Graph Kernels: Hardness Results and Efficient Alternatives. 129-143
- Ilya Desyatnikov, Ron Meir: Data-Dependent Bounds for Multi-category Classification Based on Convex Losses. 159-172
Poster Session 1
- Marina Meila: Comparing Clusterings by the Variation of Information. 173-187
- Fei Sha, Lawrence K. Saul, Daniel D. Lee: Multiplicative Updates for Large Margin Classifiers. 188-202
- David A. McAllester: Simplified PAC-Bayesian Margin Bounds. 203-215
- Shantanu Chakrabartty, Gert Cauwenberghs, Jayadeva: Sparse Probability Regression by Label Partitioning. 231-242
- Balázs Kégl: Robust Regression by Boosting the Median. 258-272
- Jaz S. Kandola, Thore Graepel, John Shawe-Taylor: Reducing Kernel Matrix Diagonal Dominance Using Semi-definite Programming. 288-302
Statistical Learning Theory
- Alexandre B. Tsybakov: Optimal Rates of Aggregation. 303-313
- Ulrike von Luxburg, Olivier Bousquet: Distance-Based Classification with Lipschitz Functions. 314-328
Online Learning
- Vladimir Vovk: Universal Well-Calibrated Algorithm for On-Line Classification. 358-372
- Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile: Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling. 373-387
Other Approaches
- Shie Mannor, John N. Tsitsiklis: Lower Bounds on the Sample Complexity of Exploration in the Multi-armed Bandit Problem. 418-432
- Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer: Smooth e-Intensive Regression by Loss Symmetrization. 433-447
Poster Session 2
- Vladimir Koltchinskii, Dmitry Panchenko, Savina Andonova: Generalization Bounds for Voting Classifiers Based on Sparsity and Clustering. 492-505
- Marcus Hutter: Sequence Prediction Based on Monotone Complexity. 506-521
- Marta Arias, Roni Khardon, Rocco A. Servedio: Polynomial Certificates for Propositional Classes. 537-551
- Ran Gilad-Bachrach, Amir Navot, Naftali Tishby: An Information Theoretic Tradeoff between Complexity and Accuracy. 595-609
- Jeffrey C. Jackson, Rocco A. Servedio: Learning Random Log-Depth Decision Trees under the Uniform Distribution. 610-624
- Aharon Bar-Hillel, Daphna Weinshall: Learning with Equivalence Constraints and the Relation to Multiclass Learning. 640-654
Target Area: Natural Language Processing
- Michael Collins: Tutorial: Machine Learning Methods in Natural Language Processing. 655
Invited Talks
- Mehryar Mohri: Learning from Uncertain Data. 656-670
- Mark Johnson: Learning and Parsing Stochastic Unification-Based Grammars. 671-683
Inductive Inference Learning
- John Case, Keh-Jiann Chen, Sanjay Jain, Wolfgang Merkle, James S. Royer: Generality's Price: Inescapable Deficiencies in Machine-Learned Programs. 684-698
- John Case, Sanjay Jain, Franco Montagna, Giulia Simi, Andrea Sorbi: On Learning to Coordinate: Random Bits Help, Insightful Normal Forms, and Competency Isomorphisms. 699-713
Open Problems
- Avrim Blum: Learning a Function of r Relevant Variables. 731-733
- Sanjoy Dasgupta: Subspace Detection: A Robust Statistics Formulation. 734
- Sanjoy Dasgupta: How Fast Is k-Means? 735
- Yoav Freund, Alon Orlitsky, Prasad Santhanam, Junan Zhang: Universal Coding of Zipf Distributions. 736-737
- Marcus Hutter: An Open Problem Regarding the Convergence of Universal A Priori Probability. 738-740
- Vladimir Koltchinskii: Entropy Bounds for Restricted Convex Hulls. 741-742
- Manfred K. Warmuth: Compressing to VC Dimension Many Points. 743-744
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