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» Using Machine Learning to Focus Iterative Optimization
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GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 10 months ago
SDR: a better trigger for adaptive variance scaling in normal EDAs
Recently, advances have been made in continuous, normal– distribution–based Estimation–of–Distribution Algorithms (EDAs) by scaling the variance up from the maximum–like...
Peter A. N. Bosman, Jörn Grahl, Franz Rothlau...
DEXA
2010
Springer
177views Database» more  DEXA 2010»
15 years 5 months ago
Enhanced Foundry Production Control
Mechanical properties are the attributes that measure the faculty of a metal to withstand several loads and tensions. Specifically, ultimate tensile strength is the force a materia...
Javier Nieves, Igor Santos, Yoseba K. Penya, Felix...
152
Voted
CVPR
2012
IEEE
13 years 6 months ago
3D landmark model discovery from a registered set of organic shapes
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...
Clement Creusot, Nick Pears, Jim Austin
ICCV
2007
IEEE
16 years 6 months ago
Conditional State Space Models for Discriminative Motion Estimation
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
Minyoung Kim, Vladimir Pavlovic
NIPS
1998
15 years 5 months ago
SMEM Algorithm for Mixture Models
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Ge...