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» Investigating human-computer optimization
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TEC
2008
165views more  TEC 2008»
15 years 4 months ago
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
Shengxiang Yang, Xin Yao
165
Voted
JMLR
2012
13 years 7 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey
170
Voted
PPSN
2000
Springer
15 years 8 months ago
Optimizing through Co-evolutionary Avalanches
Abstract. We explore a new general-purpose heuristic for nding highquality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-or...
Stefan Boettcher, Allon G. Percus, Michelangelo Gr...
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
15 years 10 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang
CEC
2009
IEEE
15 years 9 months ago
Benchmarking and solving dynamic constrained problems
— Many real-world dynamic optimisation problems have constraints, and in certain cases not only the objective function changes over time, but the constraints also change as well....
Trung Thanh Nguyen, Xin Yao