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» Learning for stochastic dynamic programming
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EVOW
2012
Springer
13 years 10 months ago
Hyperparameter Tuning in Bandit-Based Adaptive Operator Selection
We are using bandit-based adaptive operator selection while autotuning parallel computer programs. The autotuning, which uses evolutionary algorithm-based stochastic sampling, take...
Maciej Pacula, Jason Ansel, Saman P. Amarasinghe, ...
ICCV
2003
IEEE
15 years 7 months ago
Tracking Articulated Hand Motion with Eigen Dynamics Analysis
This paper introduces the concept of eigen-dynamics and proposes an eigen dynamics analysis (EDA) method to learn the dynamics of natural hand motion from labelled sets of motion ...
Hanning Zhou, Thomas S. Huang
ICML
2008
IEEE
16 years 3 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
15 years 6 months ago
Behavioural GP diversity for dynamic environments: an application in hedge fund investment
We present a new mechanism for preserving phenotypic behavioural diversity in a Genetic Programming application for hedge fund portfolio optimization, and provide experimental res...
Wei Yan, Christopher D. Clack
ICASSP
2011
IEEE
14 years 6 months ago
Factor graph-based structural equilibria in dynamical games
Correlated equilibria are a generalization of Nash equilibria that permit agents to act in a correlated manner and can therefore, model learning in games. In this paper we define...
Liming Wang, Vikram Krishnamurthy, Dan Schonfeld