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07/31/2023
Accelerating Optimal Power Flow with GPUs: SIMD Abstraction of Nonlinear Programs and Condensed-Space Interior-Point Methods
This paper introduces a novel computational framework for solving altern...
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04/27/2023
Network Cascade Vulnerability using Constrained Bayesian Optimization
Measures of power grid vulnerability are often assessed by the amount of...
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03/17/2023
Scalable Physics-based Maximum Likelihood Estimation using Hierarchical Matrices
Physics-based covariance models provide a systematic way to construct co...
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03/15/2023
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field
Modern computational methods, involving highly sophisticated mathematica...
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02/12/2023
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
Gaussian processes (GPs) are an attractive class of machine learning mod...
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06/10/2022
Scalable Computations for Nonstationary Gaussian Processes
Nonstationary Gaussian process models can capture complex spatially vary...
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04/12/2022
Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems
This paper studies the trade-off between the degree of decentralization ...
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01/01/2022
Batched Second-Order Adjoint Sensitivity for Reduced Space Methods
This paper presents an efficient method for extracting the second-order ...
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09/23/2021
Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
We study nonlinear optimization problems with stochastic objective and d...
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06/28/2021
Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition
We present the implementation of a trust-region Newton algorithm ExaTron...
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04/19/2021
Randomized Algorithms for Scientific Computing (RASC)
Randomized algorithms have propelled advances in artificial intelligence...
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02/10/2021
An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
We consider the problem of solving nonlinear optimization programs with ...
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01/27/2021
Convergence Analysis of Fixed Point Chance Constrained Optimal Power Flow Problems
For optimal power flow problems with chance constraints, a particularly ...
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07/22/2020
Flexible nonstationary spatio-temporal modeling of high-frequency monitoring data
Many physical datasets are generated by collections of instruments that ...
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05/14/2020
Overlapping Schwarz Decomposition for Nonlinear Optimal Control
We present an overlapping Schwarz decomposition algorithm for solving no...
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01/31/2020
Efficient computation of extreme excursion probabilities for dynamical systems
We develop a novel computational method for evaluating the extreme excur...
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01/11/2020
Superconvergence of Online Optimization for Model Predictive Control
We develop a one-Newton-step-per-horizon, online, lag-L, model predictiv...
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12/16/2019
A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure
In this work, cascading transmission line failures are studied through a...
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12/13/2019
Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming
In this paper, we study the sensitivity of discrete-time dynamic program...
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12/13/2019
Solving Optimal Experimental Design with Sequential Quadratic Programming and Chebyshev Interpolation
We propose an optimization algorithm to compute the optimal sensor locat...
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09/08/2019
Distributionally Robust Optimization with Correlated Data from Vector Autoregressive Processes
We present a distributionally robust formulation of a stochastic optimiz...
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08/09/2018
Scalable Gaussian Process Computations Using Hierarchical Matrices
We present a kernel-independent method that applies hierarchical matrice...
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06/06/2018
Simulating the stochastic dynamics and cascade failure of power networks
For large-scale power networks, the failure of particular transmission l...
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06/04/2018
