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» Self Bounding Learning Algorithms
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84
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IPL
2010
92views more  IPL 2010»
14 years 11 months ago
Learning parities in the mistake-bound model
We study the problem of learning parity functions that depend on at most k variables (kparities) attribute-efficiently in the mistake-bound model. We design a simple, deterministi...
Harry Buhrman, David García-Soriano, Arie M...
TCS
2010
14 years 11 months ago
Maximal width learning of binary functions
This paper concerns learning binary-valued functions defined on IR, and investigates how a particular type of ‘regularity’ of hypotheses can be used to obtain better generali...
Martin Anthony, Joel Ratsaby
GI
1998
Springer
15 years 4 months ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller
95
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ALENEX
2008
133views Algorithms» more  ALENEX 2008»
15 years 2 months ago
Comparing Online Learning Algorithms to Stochastic Approaches for the Multi-Period Newsvendor Problem
The multi-period newsvendor problem describes the dilemma of a newspaper salesman--how many paper should he purchase each day to resell, when he doesn't know the demand? We d...
Shawn O'Neil, Amitabh Chaudhary
112
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FOCS
2010
IEEE
14 years 10 months ago
A Fourier-Analytic Approach to Reed-Muller Decoding
Abstract. We present a Fourier-analytic approach to list-decoding Reed-Muller codes over arbitrary finite fields. We use this to show that quadratic forms over any field are locall...
Parikshit Gopalan