Boosting a Weak Learning Algorithm By Majority (1995)

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by Yoav Freund
Citations:417 - 15 self

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18 Data Filtering and Distribution Modeling Algorithms for Machine Learning – Yoav Freund, Manfred K. Warmuth, David Haussler, David P. Helmbold - 1993
Computational Learning Theory – Sally A. Goldman
!()+, -./01 23456 – Department Of Computer, David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass, Technische Universitaet Graz - 1995
18 Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants – Martin Anthony - 1997
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.
22 Learning From a Consistently Ignorant Teacher – Michael Frazier, Sally Goldman, Nina Mishra, Leonard Pitt - 1994
6 Efficient Learning from Faulty Data – Scott Evan Decatur - 1995
28 Learning With Unreliable Boundary Queries – Avrim Blum, Prasad Chalasani, Sally A. Goldman, Donna K. Slonim - 1995
4 Part 1: Overview of the Probably Approximately Correct (PAC) Learning Framework – David Haussler - 1995
5 Learning with Limited Visibility – Eli Dichterman - 1998
7 Some Discriminant-Based PAC Algorithms – Paul W. Goldberg - 2006
564 A Short Introduction to Boosting – Yoav Freund, Robert E. Schapire - 1999
45 General Bounds on Statistical Query Learning and PAC Learning with Noise via Hypothesis Boosting – Javed A. Aslam, Scott E. Decaturt - 1993
69 Extracting Comprehensible Models from Trained Neural Networks – W. Craven - 1996
5 On the Learnability of Discrete Distributions (Extended Abstract) – Michael Kearns, Yishay Mansour, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie - 1994
38 Boosting and hard-core sets – Adam R. Klivans, Rocco A. Servedio - 1999
667 The strength of weak learnability – Robert E. Schapire - 1990
17 More Theorems about Scale-sensitive Dimensions and Learning – Peter Bartlett, Philip M. Long - 1995