COLT 2000 - PDF Preprint Papers

COLT 2000 Annual Workshop on Computational Learning Theory

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COLT
2000
Springer

170views Machine Learning» more COLT 2000»

MadaBoost: A Modification of AdaBoost

13 years 9 months ago

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Carlos Domingo, Osamu Watanabe

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Id	Views	Title	Status

1	170	MadaBoost: A Modification of AdaBoost	claim
2	136	On the Learnability and Design of Output Codes for Multiclass Problems	claim
3	134	On the Convergence Rate of Good-Turing Estimators	claim
4	133	Adaptive and Self-Confident On-Line Learning Algorithms	claim
5	132	Barrier Boosting	claim
6	129	Average-Case Complexity of Learning Polynomials	claim
7	124	Entropy Numbers of Linear Function Classes	claim
8	121	Bias-Variance Error Bounds for Temporal Difference Updates	claim
9	121	Boosting Using Branching Programs	claim
10	121	The Role of Critical Sets in Vapnik-Chervonenkis Theory	claim
11	114	Continuous Drifting Games	claim
12	110	Model Selection and Error Estimation	claim
13	109	Computable Shell Decomposition Bounds	claim
14	99	Logistic Regression, AdaBoost and Bregman Distances	claim
15	98	PAC Analogues of Perceptron and Winnow via Boosting the Margin	claim
16	95	Relative Expected Instantaneous Loss Bounds	claim
17	88	Leveraging for Regression	claim
18	87	Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning	claim
19	81	On the Difficulty of Approximately Maximizing Agreements	claim
20	72	Improved Algorithms for Theory Revision with Queries	claim
21	62	The Computational Complexity of Densest Region Detection	claim

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