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NIPS
1996
13 years 9 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
CDC
2009
IEEE
147views Control Systems» more  CDC 2009»
14 years 10 days ago
A simulation-based method for aggregating Markov chains
— This paper addresses model reduction for a Markov chain on a large state space. A simulation-based framework is introduced to perform state aggregation of the Markov chain base...
Kun Deng, Prashant G. Mehta, Sean P. Meyn
ANOR
2005
81views more  ANOR 2005»
13 years 7 months ago
Managing Stochastic, Finite Capacity, Multi-Project Systems through the Cross-Entropy Methodology
This paper addresses the problem of loading a finite capacity, stochastic (random) and dynamic multi-project system. The system is controlled by keeping a constant number of projec...
Izack Cohen, Boaz Golany, Avraham Shtub
SIAMSC
2010
198views more  SIAMSC 2010»
13 years 6 months ago
Analysis of Block Parareal Preconditioners for Parabolic Optimal Control Problems
In this paper, we describe block matrix algorithms for the iterative solution of large scale linear-quadratic optimal control problems arising from the optimal control of parabolic...
Tarek P. Mathew, Marcus Sarkis, Christian E. Schae...
UAI
2003
13 years 9 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...