Sample compression, learnability, and the Vapnik-Chervonenkis dimension (1995)

Cached

Download Links

by Sally Floyd , Manfred Warmuth
Venue:MACHINE LEARNING
Citations:61 - 3 self

Active Bibliography

4 Part 1: Overview of the Probably Approximately Correct (PAC) Learning Framework – David Haussler - 1995
18 Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants – Martin Anthony - 1997
Computational Learning Theory – Sally A. Goldman
14 The Power of Self-Directed Learning – Sally A. Goldman, Robert H. Sloan - 1991
6 Efficient Learning from Faulty Data – Scott Evan Decatur - 1995
68 Tracking drifting concepts by minimizing disagreements – David P. Helmbold, Philip M. Long, Ming Li, Leslie Valiant - 1994
10 Simulating Access to Hidden Information while Learning – Peter Auer, Philip M. Long - 1994
Exploring Applications of Learning Theory to Pattern Matching and Dynamic Adjustment of TCP Acknowledgment Delays – Stephen Donald Scott - 1998
Dynamic Adjustment of TCP Acknowledgment Delays – n.n.
9 Noise-Tolerant Parallel Learning of Geometric Concepts – Nader H. Bshouty, Sally A. Goldman, H. David Mathias - 1995
18 Data Filtering and Distribution Modeling Algorithms for Machine Learning – Yoav Freund, Manfred K. Warmuth, David Haussler, David P. Helmbold - 1993
18 How Well do Bayes Methods Work for On-Line Prediction of {±1} values? – D. Haussler, A. Barron - 1992
17 Pattern classification and learning theory – Gabor Lugosi
45 General Bounds on Statistical Query Learning and PAC Learning with Noise via Hypothesis Boosting – Javed A. Aslam, Scott E. Decaturt - 1993
108 Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension – David Haussler, Michael Kearns, Robert Schapire - 1994
1 On the Sample Complexity of Weakly Learning – Sally A. Goldman, Michael J. Kearns, Robert E. Schapire - 1992
2 Separating Formal Bounds from Practical Performance in Learning Systems – David Cohn - 1992
1 P-sufficient statistics for PAC learning k-term-DNF formulas through enumeration. – B. Apolloni, C. Gentile
3 New Theoretical Frameworks for Machine Learning – Maria-florina Balcan, Manuel Blum, Yishay Mansour, Tom Mitchell, Santosh Vempala - 2007