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» Learning DNF by Approximating Inclusion-Exclusion Formulae
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STOC
2006
ACM
170views Algorithms» more  STOC 2006»
14 years 5 months ago
Hardness of approximate two-level logic minimization and PAC learning with membership queries
Producing a small DNF expression consistent with given data is a classical problem in computer science that occurs in a number of forms and has numerous applications. We consider ...
Vitaly Feldman
FOCS
2008
IEEE
13 years 11 months ago
Hardness of Minimizing and Learning DNF Expressions
We study the problem of finding the minimum size DNF formula for a function f : {0, 1}d → {0, 1} given its truth table. We show that unless NP ⊆ DTIME(npoly(log n) ), there i...
Subhash Khot, Rishi Saket
JCSS
2007
85views more  JCSS 2007»
13 years 5 months ago
A general dimension for query learning
We introduce a combinatorial dimension that characterizes the number of queries needed to exactly (or approximately) learn concept classes in various models. Our general dimension...
José L. Balcázar, Jorge Castro, Davi...
STOC
1994
ACM
128views Algorithms» more  STOC 1994»
13 years 9 months ago
Weakly learning DNF and characterizing statistical query learning using Fourier analysis
We present new results on the well-studied problem of learning DNF expressions. We prove that an algorithm due to Kushilevitz and Mansour [13] can be used to weakly learn DNF form...
Avrim Blum, Merrick L. Furst, Jeffrey C. Jackson, ...