COLT 2001 - PDF Preprint Papers

COLT 2001 Annual Workshop on Computational Learning Theory

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COLT
2001
Springer

165views Machine Learning» more COLT 2001»

Agnostic Boosting

13 years 9 months ago

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We prove strong noise-tolerance properties of a potential-based boosting algorithm, similar to MadaBoost (Domingo and Watanabe, 2000) and SmoothBoost (Servedio, 2003). Our analysi...

Shai Ben-David, Philip M. Long, Yishay Mansour

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Id	Views	Title	Status

1	165	Agnostic Boosting	claim
2	144	Ultraconservative Online Algorithms for Multiclass Problems	claim
3	123	Data-Dependent Margin-Based Generalization Bounds for Classification	claim
4	123	Robust Learning - Rich and Poor	claim
5	122	Limitations of Learning via Embeddings in Euclidean Half-Spaces	claim
6	122	On Agnostic Learning with {0, *, 1}-Valued and Real-Valued Hypotheses	claim
7	116	On Using Extended Statistical Queries to Avoid Membership Queries	claim
8	111	Intrinsic Complexity of Learning Geometrical Concepts from Positive Data	claim
9	110	On the Synthesis of Strategies Identifying Recursive Functions	claim
10	103	Geometric Bounds for Generalization in Boosting	claim
11	102	A Generalized Representer Theorem	claim
12	101	On Learning Monotone DNF under Product Distributions	claim
13	100	Learning Additive Models Online with Fast Evaluating Kernels	claim
14	98	Smooth Boosting and Learning with Malicious Noise	claim
15	95	Rademacher and Gaussian Complexities: Risk Bounds and Structural Results	claim
16	94	Learning Monotone DNF from a Teacher That Almost Does Not Answer Membership Queries	claim
17	87	Tracking a Small Set of Experts by Mixing Past Posteriors	claim
18	84	Learning Rates for Q-Learning	claim
19	80	A Theoretical Analysis of Query Selection for Collaborative Filtering	claim

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