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Publication search results
found 37 matches
- 1999
- Elias Abboud, Nader Agha, Nader H. Bshouty, Nizar Radwan, Fathi Saleh:
Learning Threshold Functions with Small Weights Using Membership Queries. COLT 1999: 318-322 - Chamy Allenberg:
Individual Sequence Prediction - Upper Bounds and Application for Complexity. COLT 1999: 233-242 - Thomas R. Amoth, Paul Cull, Prasad Tadepalli
:
Exact Learning of Unordered Tree Patterns from Queries. COLT 1999: 323-332 - Avrim Blum, Adam Kalai, John Langford:
Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation. COLT 1999: 203-208 - Nader H. Bshouty, Jeffrey C. Jackson, Christino Tamon:
Uniform-Distribution Attribute Noise Learnability. COLT 1999: 75-80 - Nader H. Bshouty, Jeffrey C. Jackson, Christino Tamon:
More Efficient PAC-Learning of DNF with Membership Queries Under the Uniform Distribution. COLT 1999: 286-295 - Nader H. Bshouty, David K. Wilson:
On Learning in the Presence of Unspecified Attribute Values. COLT 1999: 81-87 - Nicolò Cesa-Bianchi, Gábor Lugosi:
Minimax Regret Under log Loss for General Classes of Experts. COLT 1999: 12-18 - Yoav Freund:
An Adaptive Version of the Boost by Majority Algorithm. COLT 1999: 102-113 - Yoav Freund, Yishay Mansour:
Estimating a Mixture of Two Product Distributions. COLT 1999: 53-62 - David Gamarnik:
Extension of the PAC Framework to Finite and Countable Markov Chains. COLT 1999: 308-317 - Claudio Gentile, Nick Littlestone:
The Robustness of the p-Norm Algorithms. COLT 1999: 1-11 - Paul W. Goldberg
:
Learning Fixed-Dimension Linear Thresholds from Fragmented Data. COLT 1999: 88-99 - Geoffrey J. Gordon:
Regret Bounds for Prediction Problems. COLT 1999: 29-40 - Peter Grünwald:
Viewing all Models as "Probabilistic". COLT 1999: 171-182 - Ying Guo, Peter L. Bartlett, John Shawe-Taylor
, Robert C. Williamson:
Covering Numbers for Support Vector Machines. COLT 1999: 267-277 - Venkatesan Guruswami, Amit Sahai:
Multiclass Learning, Boosting, and Error-Correcting Codes. COLT 1999: 145-155 - Sanjay Jain, Arun Sharma:
On a Generalized Notion of Mistake Bounds. COLT 1999: 249-256 - Yuri Kalnishkan:
Linear Relations between Square-Loss and Kolmogorov Complexity. COLT 1999: 226-232 - Efim B. Kinber, Christophe Papazian, Carl H. Smith, Rolf Wiehagen:
On the Intrinsic Complexity of Learning Recursive Functions. COLT 1999: 257-266 - Jyrki Kivinen, Manfred K. Warmuth:
Boosting as Entropy Projection. COLT 1999: 134-144 - Stephen Kwek:
An Apprentice Learning Model (extended abstract). COLT 1999: 63-74 - John D. Lafferty:
Additive Models, Boosting, and Inference for Generalized Divergences. COLT 1999: 125-133 - John Langford, Avrim Blum:
Microchoice Bounds and Self Bounding Learning Algorithms. COLT 1999: 209-214 - Yishay Mansour:
Reinforcement Learning and Mistake Bounded Algorithms. COLT 1999: 183-192 - David A. McAllester:
PAC-Bayesian Model Averaging. COLT 1999: 164-170 - Atsuyoshi Nakamura:
Learning Specialist Decision Lists. COLT 1999: 215-225 - Robert E. Schapire:
Drifting Games. COLT 1999: 114-124 - Rocco A. Servedio:
On PAC Learning Using Winnow, Perceptron, and a Perceptron-like Algorithm. COLT 1999: 296-307 - John Shawe-Taylor
, Nello Cristianini:
Further Results on the Margin Distribution. COLT 1999: 278-285
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