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» An ASM-Characterization of a Class of Distributed Algorithms
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TNN
2010
234views Management» more  TNN 2010»
14 years 4 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
JAIR
2008
103views more  JAIR 2008»
14 years 9 months ago
SATzilla: Portfolio-based Algorithm Selection for SAT
It has been widely observed that there is no single "dominant" SAT solver; instead, different solvers perform best on different instances. Rather than following the trad...
Lin Xu, Frank Hutter, Holger H. Hoos, Kevin Leyton...
APPROX
2008
Springer
72views Algorithms» more  APPROX 2008»
14 years 11 months ago
Increasing the Output Length of Zero-Error Dispersers
Let C be a class of probability distributions over a finite set . A function D : {0, 1}m is a disperser for C with entropy threshold k and error if for any distribution X in C s...
Ariel Gabizon, Ronen Shaltiel
NIPS
2008
14 years 11 months ago
Integrating Locally Learned Causal Structures with Overlapping Variables
In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset. While there are asymptotically correct...
Robert E. Tillman, David Danks, Clark Glymour
COLT
2001
Springer
15 years 2 months ago
On Using Extended Statistical Queries to Avoid Membership Queries
The Kushilevitz-Mansour (KM) algorithm is an algorithm that finds all the “large” Fourier coefficients of a Boolean function. It is the main tool for learning decision trees ...
Nader H. Bshouty, Vitaly Feldman