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JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
MST
2010
155views more  MST 2010»
13 years 2 months ago
Stochastic Models and Adaptive Algorithms for Energy Balance in Sensor Networks
We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment...
Pierre Leone, Sotiris E. Nikoletseas, José ...
CEC
2010
IEEE
13 years 9 months ago
A Mean-Variance Optimization algorithm
A new stochastic optimization algorithm referred to by the authors as the `Mean-Variance Optimization' (MVO) algorithm is presented in this paper. MVO falls into the category ...
Istvan Erlich, Ganesh K. Venayagamoorthy, Nakawiro...
COCO
1994
Springer
140views Algorithms» more  COCO 1994»
14 years 2 days ago
Random Debaters and the Hardness of Approximating Stochastic Functions
A probabilistically checkable debate system (PCDS) for a language L consists of a probabilisticpolynomial-time veri er V and a debate between Player 1, who claims that the input x ...
Anne Condon, Joan Feigenbaum, Carsten Lund, Peter ...
JMLR
2010
148views more  JMLR 2010»
13 years 2 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal