
Inequality Constrained Stochastic Nonlinear Optimization via ActiveSet Sequential Quadratic Programming
We study nonlinear optimization problems with stochastic objective and d...
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Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition
We present the implementation of a trustregion Newton algorithm ExaTron...
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Randomized Algorithms for Scientific Computing (RASC)
Randomized algorithms have propelled advances in artificial intelligence...
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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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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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Flexible nonstationary spatiotemporal modeling of highfrequency monitoring data
Many physical datasets are generated by collections of instruments that ...
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Overlapping Schwarz Decomposition for Nonlinear Optimal Control
We present an overlapping Schwarz decomposition algorithm for solving no...
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Efficient computation of extreme excursion probabilities for dynamical systems
We develop a novel computational method for evaluating the extreme excur...
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Superconvergence of Online Optimization for Model Predictive Control
We develop a oneNewtonstepperhorizon, online, lagL, model predictiv...
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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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Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming
In this paper, we study the sensitivity of discretetime dynamic program...
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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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Distributionally Robust Optimization with Correlated Data from Vector Autoregressive Processes
We present a distributionally robust formulation of a stochastic optimiz...
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Scalable Gaussian Process Computations Using Hierarchical Matrices
We present a kernelindependent method that applies hierarchical matrice...
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Simulating the stochastic dynamics and cascade failure of power networks
For largescale power networks, the failure of particular transmission l...
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A Fast Algorithm for Maximum Likelihood Estimation of Mixture Proportions Using Sequential Quadratic Programming
Maximum likelihood estimation of mixture proportions has a long history ...
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Mihai Anitescu
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