Search Results for author: Mihai Anitescu

Found 13 papers, 6 papers with code

Voltage-Dependent Electromechanical Wave Propagation Modeling for Dynamic Stability Analysis in Power Systems

no code implementations21 Nov 2023 Somayeh Yarahmadi, Daniel Adrian Maldonado, Lamine Mili, Junbo Zhao, Mihai Anitescu

Analyzing these characteristics enables the assessment of the impacts of EMW on the performance of the protection system.

Network Cascade Vulnerability using Constrained Bayesian Optimization

no code implementations27 Apr 2023 Albert Lam, Mihai Anitescu, Anirudh Subramanyam

Measures of power grid vulnerability are often assessed by the amount of damage an adversary can exact on the network.

Bayesian Optimization

Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field

no code implementations15 Mar 2023 Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi, Anindya Bhaduri, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang

Modern computational methods, involving highly sophisticated mathematical formulations, enable several tasks like modeling complex physical phenomenon, predicting key properties and design optimization.

Uncertainty Quantification

Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning

1 code implementation12 Feb 2023 Zehao Niu, Mihai Anitescu, Jie Chen

Gaussian processes (GPs) are an attractive class of machine learning models because of their simplicity and flexibility as building blocks of more complex Bayesian models.

Gaussian Processes Graph Neural Network +1

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems

1 code implementation12 Apr 2022 Sungho Shin, Yiheng Lin, Guannan Qu, Adam Wierman, Mihai Anitescu

This paper studies the trade-off between the degree of decentralization and the performance of a distributed controller in a linear-quadratic control setting.

Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming

1 code implementation23 Sep 2021 Sen Na, Mihai Anitescu, Mladen Kolar

We study nonlinear optimization problems with a stochastic objective and deterministic equality and inequality constraints, which emerge in numerous applications including finance, manufacturing, power systems and, recently, deep neural networks.

An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians

1 code implementation10 Feb 2021 Sen Na, Mihai Anitescu, Mladen Kolar

Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified.

Exponential Decay of Sensitivity in Graph-Structured Nonlinear Programs

no code implementations8 Jan 2021 Sungho Shin, Mihai Anitescu, Victor M. Zavala

We study solution sensitivity for nonlinear programs (NLPs) whose structures are induced by graphs.

Stochastic Optimization Optimization and Control

On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control

no code implementations14 May 2020 Sen Na, Sungho Shin, Mihai Anitescu, Victor M. Zavala

We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs).

Motion Planning

Distributionally Robust Optimization with Correlated Data from Vector Autoregressive Processes

no code implementations8 Sep 2019 Xialiang Dou, Mihai Anitescu

We present a distributionally robust formulation of a stochastic optimization problem for non-i. i. d vector autoregressive data.

Stochastic Optimization

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