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CDC
2010
IEEE
112views Control Systems» more  CDC 2010»
13 years 2 months ago
Online Convex Programming and regularization in adaptive control
Online Convex Programming (OCP) is a recently developed model of sequential decision-making in the presence of time-varying uncertainty. In this framework, a decisionmaker selects ...
Maxim Raginsky, Alexander Rakhlin, Serdar Yük...
EAAI
2008
128views more  EAAI 2008»
13 years 7 months ago
Dual heuristic programming based nonlinear optimal control for a synchronous generator
This paper presents the design of an infinite horizon nonlinear optimal neurocontroller that replaces the conventional automatic voltage regulator and the turbine governor (CONVC)...
Jung-Wook Park, Ronald G. Harley, Ganesh K. Venaya...
ICCAD
2006
IEEE
127views Hardware» more  ICCAD 2006»
14 years 4 months ago
Joint design-time and post-silicon minimization of parametric yield loss using adjustable robust optimization
Parametric yield loss due to variability can be effectively reduced by both design-time optimization strategies and by adjusting circuit parameters to the realizations of variable...
Murari Mani, Ashish Kumar Singh, Michael Orshansky
NIPS
1998
13 years 9 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
CCR
2000
96views more  CCR 2000»
13 years 7 months ago
Decentralized optimal traffic engineering in the internet
Distributed optimal traffic engineering in the presence of multiple paths has been found to be a difficult problem to solve. In this paper, we introduce a new approach in an attem...
Constantino M. Lagoa, Hao Che