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GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
14 years 3 months ago
Markov chain models of bare-bones particle swarm optimizers
We apply a novel theoretical approach to better understand the behaviour of different types of bare-bones PSOs. It avoids many common but unrealistic assumptions often used in an...
Riccardo Poli, William B. Langdon
JMLR
2006
89views more  JMLR 2006»
13 years 9 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
LATINCRYPT
2010
13 years 7 months ago
Accelerating Lattice Reduction with FPGAs
We describe an FPGA accelerator for the Kannan–Fincke– Pohst enumeration algorithm (KFP) solving the Shortest Lattice Vector Problem (SVP). This is the first FPGA implementati...
Jérémie Detrey, Guillaume Hanrot, Xa...
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
14 years 3 months ago
Articulating user preferences in many-objective problems by sampling the weighted hypervolume
The hypervolume indicator has become popular in recent years both for performance assessment and to guide the search of evolutionary multiobjective optimizers. Two critical resear...
Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart...
ANTSW
2004
Springer
14 years 2 months ago
S-ACO: An Ant-Based Approach to Combinatorial Optimization Under Uncertainty
A general-purpose, simulation-based algorithm S-ACO for solving stochastic combinatorial optimization problems by means of the ant colony optimization (ACO) paradigm is investigate...
Walter J. Gutjahr