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JMLR
2012
11 years 11 months ago
SpeedBoost: Anytime Prediction with Uniform Near-Optimality
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Alexander Grubb, Drew Bagnell
ACG
2006
Springer
14 years 2 months ago
RSPSA: Enhanced Parameter Optimization in Games
Most game programs have a large number of parameters that are crucial for their performance. Tuning these parameters by hand is rather difficult. Therefore automatic optimization a...
Levente Kocsis, Csaba Szepesvári, Mark H. M...
CEC
2007
IEEE
14 years 3 months ago
Computational intelligence algorithms for risk-adjusted trading strategies
Abstract— This paper investigates the performance of trading strategies identified through Computational Intelligence techniques. We focus on trading rules derived by Genetic Pr...
Nicos G. Pavlidis, E. G. Pavlidis, Michael G. Epit...
ICSM
1994
IEEE
14 years 1 months ago
A Framework for Partial Data Flow Analysis
Although data pow analysis was first developed for use in compilers, its usefulness is now recognized in many software tools. Because of its compiler origins, the computation of d...
Rajiv Gupta, Mary Lou Soffa
MMB
2012
Springer
259views Communications» more  MMB 2012»
12 years 4 months ago
Boosting Design Space Explorations with Existing or Automatically Learned Knowledge
Abstract. During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with h...
Ralf Jahr, Horia Calborean, Lucian Vintan, Theo Un...