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» A Generalization of Forward-Backward Algorithm
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TCS
2010
15 years 1 months ago
Parametric random generation of deterministic tree automata
Uniform random generators deliver a simple empirical means to estimate the average complexity of an algorithm. We present a general rejection algorithm that generates sequential l...
Pierre-Cyrille Héam, Cyril Nicaud, Sylvain ...
DAC
2012
ACM
13 years 9 months ago
ComPLx: A Competitive Primal-dual Lagrange Optimization for Global Placement
We develop a projected-subgradient primal-dual Lagrange optimization for global placement, that can be instantiated with a variety of interconnect models. It decomposes the origin...
Myung-Chul Kim, Igor L. Markov
GECCO
2006
Springer
140views Optimization» more  GECCO 2006»
15 years 10 months ago
Prediction update algorithms for XCSF: RLS, Kalman filter, and gain adaptation
We study how different prediction update algorithms influence the performance of XCSF. We consider three classical parameter estimation algorithms (NLMS, RLS, and Kalman filter) a...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
PODC
2009
ACM
16 years 7 months ago
Distributed and parallel algorithms for weighted vertex cover and other covering problems
The paper presents distributed and parallel -approximation algorithms for covering problems, where is the maximum number of variables on which any constraint depends (for example...
Christos Koufogiannakis, Neal E. Young
ML
2007
ACM
106views Machine Learning» more  ML 2007»
15 years 6 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung