COLT A*

37 papers

YearTitle / Authors
1999Additive Models, Boosting, and Inference for Generalized Divergences.
John D. Lafferty
1999An Adaptive Version of the Boost by Majority Algorithm.
Yoav Freund
1999An Apprentice Learning Model (extended abstract).
Stephen Kwek
1999Approximation Algorithms for Clustering Problems.
David B. Shmoys
1999Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation.
Avrim Blum, Adam Kalai, John Langford
1999Boosting as Entropy Projection.
Jyrki Kivinen, Manfred K. Warmuth
1999Convergence Analysis of Temporal-Difference Learning Algorithms with Linear Function Approximation.
Vladislav Tadic
1999Covering Numbers for Support Vector Machines.
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Robert C. Williamson
1999Drifting Games.
Robert E. Schapire
1999Estimating a Mixture of Two Product Distributions.
Yoav Freund, Yishay Mansour
1999Exact Learning of Unordered Tree Patterns from Queries.
Thomas R. Amoth, Paul Cull, Prasad Tadepalli
1999Extension of the PAC Framework to Finite and Countable Markov Chains.
David Gamarnik
1999Extensional Set Learning (extended abstract).
Sebastiaan Terwijn
1999Further Results on the Margin Distribution.
John Shawe-Taylor, Nello Cristianini
1999Individual Sequence Prediction - Upper Bounds and Application for Complexity.
Chamy Allenberg
1999Learning Fixed-Dimension Linear Thresholds from Fragmented Data.
Paul W. Goldberg
1999Learning Specialist Decision Lists.
Atsuyoshi Nakamura
1999Learning Threshold Functions with Small Weights Using Membership Queries.
Elias Abboud, Nader Agha, Nader H. Bshouty, Nizar Radwan, Fathi Saleh
1999Linear Relations between Square-Loss and Kolmogorov Complexity.
Yuri Kalnishkan
1999Microchoice Bounds and Self Bounding Learning Algorithms.
John Langford, Avrim Blum
1999Minimax Regret Under log Loss for General Classes of Experts.
Nicolò Cesa-Bianchi, Gábor Lugosi
1999More Efficient PAC-Learning of DNF with Membership Queries Under the Uniform Distribution.
Nader H. Bshouty, Jeffrey C. Jackson, Christino Tamon
1999Multiclass Learning, Boosting, and Error-Correcting Codes.
Venkatesan Guruswami, Amit Sahai
1999On Learning in the Presence of Unspecified Attribute Values.
Nader H. Bshouty, David K. Wilson
1999On PAC Learning Using Winnow, Perceptron, and a Perceptron-like Algorithm.
Rocco A. Servedio
1999On Prediction of Individual Sequences Relative to a Set of Experts in the Presence of Noise.
Tsachy Weissman, Neri Merhav
1999On Theory Revision with Queries.
Robert H. Sloan, György Turán
1999On a Generalized Notion of Mistake Bounds.
Sanjay Jain, Arun Sharma
1999On the Intrinsic Complexity of Learning Recursive Functions.
Efim B. Kinber, Christophe Papazian, Carl H. Smith, Rolf Wiehagen
1999PAC-Bayesian Model Averaging.
David A. McAllester
1999Proceedings of the Twelfth Annual Conference on Computational Learning Theory, COLT 1999, Santa Cruz, CA, USA, July 7-9, 1999
Shai Ben-David, Philip M. Long
1999Regret Bounds for Prediction Problems.
Geoffrey J. Gordon
1999Reinforcement Learning and Mistake Bounded Algorithms.
Yishay Mansour
1999The Robustness of the
Claudio Gentile, Nick Littlestone
1999Theoretical Analysis of a Class of Randomized Regularization Methods.
Tong Zhang
1999Uniform-Distribution Attribute Noise Learnability.
Nader H. Bshouty, Jeffrey C. Jackson, Christino Tamon
1999Viewing all Models as "Probabilistic".
Peter Grünwald