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» Function Optimization with Coevolutionary Algorithms
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JMLR
2012
13 years 3 months ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
CDC
2009
IEEE
173views Control Systems» more  CDC 2009»
15 years 5 months ago
Optimality of affine policies in multi-stage robust optimization
In this paper, we show the optimality of a certain class of disturbance-affine control policies in the context of one-dimensional, constrained, multi-stage robust optimization. Ou...
Dimitris Bertsimas, Dan Andrei Iancu, Pablo A. Par...
CEC
2007
IEEE
15 years 3 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
ICCD
2001
IEEE
119views Hardware» more  ICCD 2001»
15 years 10 months ago
A Functional Validation Technique: Biased-Random Simulation Guided by Observability-Based Coverage
We present a simulation-based semi-formal verification method for sequential circuits described at the registertransfer level. The method consists of an iterative loop where cove...
Serdar Tasiran, Farzan Fallah, David G. Chinnery, ...
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 3 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman