COLT 2003

60 papers

A General Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria Amy Greenwald, Amir Jafari

An Information Theoretic Tradeoff Between Complexity and Accuracy Ran Gilad-Bachrach, Amir Navot, Naftali Tishby

An Open Problem Regarding the Convergence of Universal a Priori Probability Marcus Hutter

Approximate Equivalence of Markov Decision Processes Eyal Even-Dar, Yishay Mansour

Bhattacharyya Expected Likelihood Kernels Tony Jebara, Risi Kondor

Boosting with Diverse Base Classifiers Sanjoy Dasgupta, Philip M. Long

Comparing Clusterings by the Variation of Information Marina Meila

Compressing to VC Dimension Many Points Manfred K. Warmuth

Data-Dependent Bounds for Multi-Category Classification Based on Convex Losses Ilya Desyatnikov, Ron Meir

Distance-Based Classification with Lipschitz Functions Ulrike von Luxburg, Olivier Bousquet

Efficient Algorithms for Online Decision Problems Adam Kalai, Santosh S. Vempala

Entropy Bounds for Restricted Convex Hulls Vladimir Koltchinskii

Exploiting Task Relatedness for Mulitple Task Learning Shai Ben-David, Reba Schuller

Fast Kernels for Inexact String Matching Christina S. Leslie, Rui Kuang

Generality's Price: Inescapable Deficiencies in Machine-Learned Programs John Case, Keh-Jiann Chen, Sanjay Jain, Wolfgang Merkle, James S. Royer

Generalization Bounds for Voting Classifiers Based on Sparsity and Clustering Vladimir Koltchinskii, Dmitry Panchenko, Savina Andonova

How Fast Is K-Means? Sanjoy Dasgupta

How Many Strings Are Easy to Predict? Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin

Internal Regret in On-Line Portfolio Selection Gilles Stoltz, Gábor Lugosi

Kernels and Regularization on Graphs Alexander J. Smola, Risi Kondor

Knowledge-Based Nonlinear Kernel Classifiers Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik

Learning a Function of R Relevant Variables Avrim Blum

Learning Algorithm for Enclosing Points in Bregmanian Spheres Koby Crammer, Yoram Singer

Learning All Subfunctions of a Function Sanjay Jain, Efim B. Kinber, Rolf Wiehagen

Learning and Parsing Stochastic Unification-Based Grammars Mark Johnson

Learning Arithmetic Circuits via Partial Derivatives Adam R. Klivans, Amir Shpilka

Learning from Uncertain Data Mehryar Mohri

Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile

Learning Random Log-Depth Decision Trees Under the Uniform Distribution Jeffrey C. Jackson, Rocco A. Servedio

Learning with Equivalence Constraints and the Relation to Multiclass Learning Aharon Bar-Hillel, Daphna Weinshall

Learning with Rigorous Support Vector Machines Jinbo Bi, Vladimir Vapnik

Lower Bounds on the Sample Complexity of Exploration in the Multi-Armed Bandit Problem Shie Mannor, John N. Tsitsiklis

Maximal Margin Classification for Metric Spaces Matthias Hein, Olivier Bousquet

Maximum Margin Algorithms with Boolean Kernels Roni Khardon, Rocco A. Servedio

Multiplicative Updates for Large Margin Classifiers Fei Sha, Lawrence K. Saul, Daniel D. Lee

On Finding Large Conjunctive Clusters Nina Mishra, Dana Ron, Ram Swaminathan

On Graph Kernels: Hardness Results and Efficient Alternatives Thomas Gärtner, Peter A. Flach, Stefan Wrobel

On Learning to Coordinate: Random Bits Help, Insightful Normal Forms, and Competency Isomorphisms John Case, Sanjay Jain, Franco Montagna, Giulia Simi, Andrea Sorbi

On-Line Learning with Imperfect Monitoring Shie Mannor, Nahum Shimkin

Optimal Rates of Aggregation Alexandre B. Tsybakov

PAC-MDL Bounds Avrim Blum, John Langford

Polynomial Certificates for Propositional Classes Marta Arias, Roni Khardon, Rocco A. Servedio

Positive Definite Rational Kernels Corinna Cortes, Patrick Haffner, Mehryar Mohri

Preference Elicitation and Query Learning Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, Martin Zinkevich

Projective DNF Formulae and Their Revision Robert H. Sloan, Balázs Szörényi, György Turán

Random Subclass Bounds Shahar Mendelson, Petra Philips

Reducing Kernel Matrix Diagonal Dominance Using Semi-Definite Programming Jaz S. Kandola, Thore Graepel, John Shawe-Taylor

Robust Regression by Boosting the Median Balázs Kégl

Sequence Prediction Based on Monotone Complexity Marcus Hutter

Simplified PAC-Bayesian Margin Bounds David A. McAllester

Smooth E-Intensive Regression by Loss Symmetrization Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer

Sparse Kernel Partial Least Squares Regression Michinari Momma, Kristin P. Bennett

Sparse Probability Regression by Label Partitioning Shantanu Chakrabartty, Gert Cauwenberghs, Jayadeva

Subspace Detection: A Robust Statistics Formulation Sanjoy Dasgupta

Tutorial: Learning Topics in Game-Theoretic Decision Making Michael L. Littman

Tutorial: Machine Learning Methods in Natural Language Processing Michael Collins

Universal Coding of Zipf Distributions Yoav Freund, Alon Orlitsky, Prasad Santhanam, Junan Zhang

Universal Well-Calibrated Algorithm for On-Line Classification Vladimir Vovk

Using a Linear Fit to Determine Monotonicity Directions Malik Magdon-Ismail, Joseph Sill

When Is Small Beautiful? Amiran Ambroladze, John Shawe-Taylor