44 citations · 250 across the 61 of their papers we have counts for
7 papers · 1 filter
Near-Optimal Performance of Stochastic Model Predictive Control
Sungho Shin, Sen Na, Mihai Anitescu
This article presents a dynamic regret analysis for stochastic model predictive control (SMPC) in linear systems with quadratic performance index and additive and multiplicative un…
Constrained Policy Optimization for Stochastic Optimal Control under Nonstationary Uncertainties
Sungho Shin, François Pacaud, Emil Contantinescu +1
This article presents a constrained policy optimization approach for the optimal control of systems under nonstationary uncertainties. We introduce an assumption that we call Marko…
Exploiting GPU/SIMD Architectures for Solving Linear-Quadratic MPC Problems
David Cole, Sungho Shin, François Pacaud +2
We report numerical results on solving constrained linear-quadratic model predictive control (MPC) problems by exploiting graphics processing units (GPUs). The presented method red…
Scalable Computations for Nonstationary Gaussian Processes
Paul G. Beckman, Christopher J. Geoga, Michael L. Stein +1
Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets…
Order-Disorder Transitions in (CaSr)RhSn
Puspa Upreti, Matthew Krogstad, Charlotte Haley +6
The classification of structural phase transitions as displacive or order-disorder in character is usually based on spectroscopic data above the transition. We use single crystal x…
Condensed interior-point methods: porting reduced-space approaches on GPU hardware
François Pacaud, Sungho Shin, Michel Schanen +2
The interior-point method (IPM) has become the workhorse method for nonlinear programming. The performance of IPM is directly related to the linear solver employed to factorize the…
Batched Second-Order Adjoint Sensitivity for Reduced Space Methods
François Pacaud, Michel Schanen, Daniel Adrian Maldonado +4
This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations on upcoming graphical processing units (GPU) dom…