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» On Learning Boolean Functions
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145
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NIPS
2000
15 years 3 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
127
Voted
BMCBI
2006
152views more  BMCBI 2006»
15 years 2 months ago
Predicting deleterious nsSNPs: an analysis of sequence and structural attributes
Background: There has been an explosion in the number of single nucleotide polymorphisms (SNPs) within public databases. In this study we focused on non-synonymous protein coding ...
Richard J. B. Dobson, Patricia B. Munroe, Mark J. ...
146
Voted
STOC
2010
ACM
200views Algorithms» more  STOC 2010»
15 years 11 months ago
Hardness Amplification in Proof Complexity
We present a generic method for converting any family of unsatisfiable CNF formulas that require large resolution rank into CNF formulas whose refutation requires large rank for p...
Paul Beame, Trinh Huynh and Toniann Pitassi
138
Voted
FSTTCS
2009
Springer
15 years 9 months ago
Fractional Pebbling and Thrifty Branching Programs
We study the branching program complexity of the tree evaluation problem, introduced in [BCM+09a] as a candidate for separating NL from LogCFL. The input to the problem is a roote...
Mark Braverman, Stephen A. Cook, Pierre McKenzie, ...
94
Voted
ICML
2006
IEEE
16 years 3 months ago
Regression with the optimised combination technique
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
Jochen Garcke