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pro vyhledávání: '"Kotsalis, Georgios"'
Publikováno v:
Open Journal of Mathematical Optimization, Vol 3, Iss , Pp 1-38 (2022)
We address the problems of computing operator norms of matrices induced by given norms on the argument and the image space. It is known that aside of a fistful of “solvable cases”, most notably, the case when both given norms are Euclidean, compu
Externí odkaz:
https://doaj.org/article/2461c5f817714b6c981e84db44dad4ba
We consider the classic stochastic linear quadratic regulator (LQR) problem under an infinite horizon average stage cost. By leveraging recent policy gradient methods from reinforcement learning, we obtain a first-order method that finds a stable fee
Externí odkaz:
http://arxiv.org/abs/2212.00084
Publikováno v:
Open Journal of Mathematical Optimization Volume 3 (2022)
We address the problems of computing operator norms of matrices induced by given norms on the argument and the image space. It is known that aside of a fistful of "solvable cases," most notably, the case when both given norms are Euclidean, computing
Externí odkaz:
http://arxiv.org/abs/2110.04389
The focus of this paper is on stochastic variational inequalities (VI) under Markovian noise. A prominent application of our algorithmic developments is the stochastic policy evaluation problem in reinforcement learning. Prior investigations in the l
Externí odkaz:
http://arxiv.org/abs/2011.08434
In this paper we first present a novel operator extrapolation (OE) method for solving deterministic variational inequality (VI) problems. Similar to the gradient (operator) projection method, OE updates one single search sequence by solving a single
Externí odkaz:
http://arxiv.org/abs/2011.02987
This work addresses the finite-horizon robust covariance control problem for discrete-time, partially observable, linear system affected by random zero mean noise and deterministic but unknown disturbances restricted to lie in what is called ellitopi
Externí odkaz:
http://arxiv.org/abs/2007.00132
Autor:
Kotsalis, Georgios, Lan, Guanghui
In this work we provide a computationally tractable procedure for designing affine control policies, applied to constrained, discrete-time, partially observable, linear systems subject to set bounded disturbances, stochastic noise and potentially Mar
Externí odkaz:
http://arxiv.org/abs/1801.00170
Autor:
Kotsalis, Georgios
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.
Includes bibliographical references (leaves 57-60).
The contribution of this thesis is the development of tractable computational methods for red
Includes bibliographical references (leaves 57-60).
The contribution of this thesis is the development of tractable computational methods for red
Externí odkaz:
http://hdl.handle.net/1721.1/38255
Autor:
Zhang, Bopeng, Kotsalis, Georgios, Khan, Jahanzeb, Xiong, Zhaoyang, Igou, Thomas, Lan, Guanghui, Chen, Yongsheng
Publikováno v:
In Journal of Membrane Science 15 October 2020 612
Akademický článek
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