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GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 4 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
ICCAD
2009
IEEE
109views Hardware» more  ICCAD 2009»
15 years 4 months ago
CRISP: Congestion reduction by iterated spreading during placement
Dramatic progress has been made in algorithms for placement and routing over the last 5 years, with improvements in both speed and quality. Combining placement and routing into a ...
Jarrod A. Roy, Natarajan Viswanathan, Gi-Joon Nam,...
SIAMCO
2011
15 years 1 months ago
Consistency of Sequential Bayesian Sampling Policies
We consider Bayesian information collection, in which a measurement policy collects information to support a future decision. This framework includes ranking and selection, continu...
Peter Frazier, Warren B. Powell
INTERSPEECH
2010
15 years 1 months ago
Investigation of full-sequence training of deep belief networks for speech recognition
Recently, Deep Belief Networks (DBNs) have been proposed for phone recognition and were found to achieve highly competitive performance. In the original DBNs, only framelevel info...
Abdel-rahman Mohamed, Dong Yu, L. Deng
SIAMIS
2010
190views more  SIAMIS 2010»
15 years 1 months ago
Analysis and Generalizations of the Linearized Bregman Method
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
Wotao Yin