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NIPS
2000
13 years 9 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
APN
2009
Springer
13 years 11 months ago
P-Semiflow Computation with Decision Diagrams
We present a symbolic method for p-semiflow computation, based on zero-suppressed decision diagrams. Both the traditional explicit methods and our new symbolic method rely on Farka...
Gianfranco Ciardo, Galen Mecham, Emmanuel Paviot-A...
VLSID
1999
IEEE
88views VLSI» more  VLSID 1999»
13 years 11 months ago
New and Exact Filling Algorithms for Layout Density Control
To reduce manufacturing variation due to chemicalmechanical polishing and to improve yield, layout must be made uniform with respect to density criteria. This is achieved by layou...
Andrew B. Kahng, Gabriel Robins, Anish Singh, Alex...
FSTTCS
2006
Springer
13 years 11 months ago
Validity Checking for Finite Automata over Linear Arithmetic Constraints
Abstract Decision procedures underlie many program analysis problems. Traditional program analysis algorithms attempt to prove some property about a single, statically-defined prog...
Gary Wassermann, Zhendong Su
ICML
2010
IEEE
13 years 8 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...