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» XCS with computed prediction for the learning of Boolean fun...
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STOC
2003
ACM
122views Algorithms» more  STOC 2003»
14 years 7 months ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
RECOMB
2012
Springer
11 years 10 months ago
Reconstructing Boolean Models of Signaling
Abstract. Since the first emergence of protein-protein interaction networks, more than a decade ago, they have been viewed as static scaffolds of the signaling-regulatory events ...
Roded Sharan, Richard M. Karp
COLT
2008
Springer
13 years 9 months ago
Almost Tight Upper Bound for Finding Fourier Coefficients of Bounded Pseudo- Boolean Functions
A pseudo-Boolean function is a real-valued function defined on {0, 1}n . A k-bounded function is a pseudo-Boolean function that can be expressed as a sum of subfunctions each of w...
Sung-Soon Choi, Kyomin Jung, Jeong Han Kim
IJCAI
1993
13 years 8 months ago
Average-Case Analysis of a Nearest Neighbor Algorithm
In this paper we present an average-case analysis of the nearest neighbor algorithm, a simple induction method that has been studied by manyresearchers. Our analysis assumes a con...
Pat Langley, Wayne Iba

Book
796views
15 years 6 months ago
Introduction to Machine Learning
This is an introductory book about machine learning. Notice that this is a draft book. It may contain typos, mistakes, etc. The book covers the following topics: Boolean Functio...
Nils J. Nilsson