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ICML
2009
IEEE
15 years 10 months ago
Using fast weights to improve persistent contrastive divergence
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
Tijmen Tieleman, Geoffrey E. Hinton
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
15 years 9 months ago
Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms
Recent research into single–objective continuous Estimation– of–Distribution Algorithms (EDAs) has shown that when maximum–likelihood estimations are used for parametric d...
Peter A. N. Bosman, Dirk Thierens
ICPR
2008
IEEE
16 years 4 months ago
On using error bounds to optimize cost-sensitive multimodal biometric authentication
While using more biometric traits in multimodal biometric fusion can effectively increase the system robustness, often, the cost associated to adding additional systems is not con...
Norman Poh, Josef Kittler
CEC
2010
IEEE
14 years 6 months ago
Evoptool: An extensible toolkit for evolutionary optimization algorithms comparison
— This paper presents Evolutionary Optimization Tool (Evoptool), an optimization toolkit that implements a set of meta-heuristics based on the Evolutionary Computation paradigm. ...
Gabriele Valentini, Luigi Malagò, Matteo Ma...
ICMCS
2006
IEEE
151views Multimedia» more  ICMCS 2006»
15 years 9 months ago
A New Oriented Adaptive Cross Search Algorithm for Block Matching Motion Estimation
Block-matching motion estimation plays an important role in video coding and faster, more robust and more effective search algorithms are needed. Recently, a great number of fast ...
Heng Yang, Qing Wang