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» Minimization of an M-convex Function
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SIAMJO
2008
212views more  SIAMJO 2008»
13 years 9 months ago
Convergence Rate of an Optimization Algorithm for Minimizing Quadratic Functions with Separable Convex Constraints
A new active set algorithm for minimizing quadratic functions with separable convex constraints is proposed by combining the conjugate gradient method with the projected gradient. ...
Radek Kucera
ICSE
2009
IEEE-ACM
14 years 4 months ago
MINTS: A general framework and tool for supporting test-suite minimization
Regression test suites tend to grow over time as new test cases are added to exercise new functionality or to target newly-discovered faults. When test suites become too large, th...
Hwa-You Hsu, Alessandro Orso
NIPS
2007
13 years 10 months ago
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization
We develop and analyze an algorithm for nonparametric estimation of divergence functionals and the density ratio of two probability distributions. Our method is based on a variati...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
TCAD
1998
86views more  TCAD 1998»
13 years 8 months ago
Fast heuristic and exact algorithms for two-level hazard-free logic minimization
None of the available minimizers for 2-level hazard-free logic minimization can synthesize very large circuits. This limitation has forced researchers to resort to manual and auto...
Michael Theobald, Steven M. Nowick
JMIV
2007
83views more  JMIV 2007»
13 years 9 months ago
Minimization of a Detail-Preserving Regularization Functional for Impulse Noise Removal
Recently, a powerful two-phase method for restoring images corrupted with high level impulse noise has been developed. The main drawback of the method is the computational efficie...
Jian-Feng Cai, Raymond H. Chan, Carmine Di Fiore