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JMLR
2006
108views more  JMLR 2006»
15 years 4 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...
JMLR
2012
13 years 7 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
GECCO
2003
Springer
139views Optimization» more  GECCO 2003»
15 years 10 months ago
Daily Stock Prediction Using Neuro-genetic Hybrids
We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
Yung-Keun Kwon, Byung Ro Moon
GECCO
2009
Springer
115views Optimization» more  GECCO 2009»
15 years 9 months ago
Benchmarking the pure random search on the BBOB-2009 testbed
We benchmark the pure random search algorithm on the BBOB 2009 noise-free testbed. Each candidate solution is sampled uniformly in [−5, 5]D , where D denotes the search space di...
Anne Auger, Raymond Ros
GECCO
2009
Springer
118views Optimization» more  GECCO 2009»
15 years 9 months ago
Benchmarking the pure random search on the BBOB-2009 noisy testbed
We benchmark the Pure-Random-Search algorithm on the BBOB 2009 noisy testbed. Each candidate solution is sampled uniformly in [−5, 5]D , where D denotes the search space dimensi...
Anne Auger, Raymond Ros