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» Introduction to Randomized Algorithms
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BMCBI
2005
201views more  BMCBI 2005»
15 years 3 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota
LATIN
2010
Springer
15 years 1 months ago
On Quadratic Threshold CSPs
A predicate P : {−1, 1}k → {0, 1} can be associated with a constraint satisfaction problem Max CSP(P). P is called “approximation resistant” if Max CSP(P) cannot be approxi...
Per Austrin, Siavosh Benabbas, Avner Magen
SIAMCOMP
2010
147views more  SIAMCOMP 2010»
15 years 1 months ago
Uniform Direct Product Theorems: Simplified, Optimized, and Derandomized
The classical direct product theorem for circuits says that if a Boolean function f : {0, 1}n → {0, 1} is somewhat hard to compute on average by small circuits, then the correspo...
Russell Impagliazzo, Ragesh Jaiswal, Valentine Kab...
SASO
2010
IEEE
15 years 1 months ago
Distributed Control for Small Customer Energy Demand Management
We present the ColoredPower algorithm, which is designed to provide collaborative electricity demand shaping for residential and small-business customers. Demand shaping for this m...
Vinayak V. Ranade, Jacob Beal
CORR
2011
Springer
192views Education» more  CORR 2011»
14 years 10 months ago
Distribution-Independent Evolvability of Linear Threshold Functions
Valiant’s (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold ...
Vitaly Feldman