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» Using Gaussian Processes to Optimize Expensive Functions
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CVIU
2011
12 years 11 months ago
Graph-based quadratic optimization: A fast evolutionary approach
Quadratic optimization lies at the very heart of many structural pattern recognition and computer vision problems, such as graph matching, object recognition, image segmentation, ...
Samuel Rota Bulò, Marcello Pelillo, Immanue...
ISM
2008
IEEE
110views Multimedia» more  ISM 2008»
14 years 2 months ago
A Hardware-Independent Fast Logarithm Approximation with Adjustable Accuracy
Many multimedia applications rely on the computation of logarithms, for example, when estimating log-likelihoods for Gaussian Mixture Models. Knowing of the demand to compute loga...
Oriol Vinyals, Gerald Friedland
HAIS
2009
Springer
14 years 7 days ago
Hybrid Evolutionary Algorithm for Solving Global Optimization Problems
Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ranked...
Radha Thangaraj, Millie Pant, Ajith Abraham, Youak...
ICML
2006
IEEE
14 years 8 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
BMCBI
2007
233views more  BMCBI 2007»
13 years 7 months ago
160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA)
Background: To infer homology and subsequently gene function, the Smith-Waterman (SW) algorithm is used to find the optimal local alignment between two sequences. When searching s...
Isaac T. S. Li, Warren Shum, Kevin Truong