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» Defining implicit objective functions for design problems
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CEC
2008
IEEE
14 years 3 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
ICCAD
1999
IEEE
120views Hardware» more  ICCAD 1999»
14 years 1 months ago
Design and optimization of LC oscillators
We present a method for optimizing and automating component and transistor sizing for CMOS LC oscillators. We observe that the performance measures can be formulated as posynomial...
Maria del Mar Hershenson, Ali Hajimiri, Sunderaraj...
WSC
2008
13 years 11 months ago
Discrete stochastic optimization using linear interpolation
We consider discrete stochastic optimization problems where the objective function can only be estimated by a simulation oracle; the oracle is defined only at the discrete points....
Honggang Wang, Bruce W. Schmeiser
DAGM
2009
Springer
14 years 3 months ago
Markerless 3D Face Tracking
We present a novel algorithm for the markerless tracking of deforming surfaces such as faces. We acquire a sequence of 3D scans along with color images at 40Hz. The data is then re...
Christian Walder, Martin Breidt, Heinrich H. B&uum...
BMCBI
2004
252views more  BMCBI 2004»
13 years 8 months ago
Applying Support Vector Machines for Gene ontology based gene function prediction
Background: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to ann...
Arunachalam Vinayagam, Rainer König, Jutta Mo...