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ML
2008
ACM
101views Machine Learning» more  ML 2008»
13 years 7 months ago
On reoptimizing multi-class classifiers
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
GECCO
2011
Springer
270views Optimization» more  GECCO 2011»
12 years 11 months ago
Geometric surrogate-based optimisation for permutation-based problems
In continuous optimisation, surrogate models (SMs) are used when tackling real-world problems whose candidate solutions are expensive to evaluate. In previous work, we showed that...
Alberto Moraglio, Yong-Hyuk Kim, Yourim Yoon
CEC
2007
IEEE
13 years 11 months ago
Efficient assembling of genome fragments using genetic algorithm enhanced by heuristic search
Abstract-- Shotgun sequencing is the state-of-the-art to decode genome sequence. However this technique needs a lot of fragments. Combining those fragments correctly requires enorm...
Satoko Kikuchi, Goutam Chakraborty
TPDS
2008
117views more  TPDS 2008»
13 years 7 months ago
Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approac
High Performance Computing data centers have been rapidly growing, both in number and size. Thermal management of data centers can address dominant problems associated with cooling...
Qinghui Tang, Sandeep K. S. Gupta, Georgios Varsam...
AISB
1994
Springer
13 years 11 months ago
Formal Memetic Algorithms
Abstract. A formal, representation-independent form of a memetic algorithm-a genetic algorithm incorporating local search--is introduced. A generalisedform of N-point crossover is ...
Nicholas J. Radcliffe, Patrick D. Surry