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NCI
2004
141views Neural Networks» more  NCI 2004»
13 years 9 months ago
Estimating the error at given test input points for linear regression
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
Masashi Sugiyama
GECCO
2005
Springer
122views Optimization» more  GECCO 2005»
14 years 1 months ago
An enhanced GA to improve the search process reliability in tuning of control systems
Evolutionary Algorithms (EAs) have been largely applied to optimisation and synthesis of controllers. In spite of several successful applications and competitive solutions, the st...
Andrea Soltoggio
HIPEAC
2005
Springer
14 years 1 months ago
A Single (Unified) Shader GPU Microarchitecture for Embedded Systems
We present and evaluate the TILA-rin GPU microarchitecture for embedded systems using the ATTILA GPU simulation framework. We use a trace from an execution of the Unreal Tournament...
Victor Moya Del Barrio, Carlos González, Jo...
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
14 years 28 days ago
Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming
We describe the first instance of an approach for control programming of humanoid robots, based on evolution as the main adaptation mechanism. In an attempt to overcome some of th...
Krister Wolff, Peter Nordin
GECCO
2010
Springer
188views Optimization» more  GECCO 2010»
13 years 11 months ago
Benchmarking real-coded genetic algorithm on noisy black-box optimization testbed
Originally, genetic algorithms were developed based on the binary representation of candidate solutions in which each conjectured solution is a fixed-length string of binary numb...
Thanh-Do Tran, Gang-Gyoo Jin