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Stochastic dual dynamic programming for multistage stochastic mixed-integer nonlinear optimization
In this paper, we study multistage stochastic mixed-integer nonlinear programs (MS-MINLP). This general class of problems encompasses, as important...
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Stochastic Composition Optimization of Functions Without Lipschitz Continuous Gradient
In this paper, we study stochastic optimization of two-level composition of functions without Lipschitz continuous gradient. The smoothness property...
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Connections between Robust Statistical Estimation, Robust Decision-Making with Two-Stage Stochastic Optimization, and Robust Machine Learning Problems
The authors discuss connections between the problems of two-stage stochastic programming, robust decision-making, robust statistical estimation, and...
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Inequality constrained stochastic nonlinear optimization via active-set sequential quadratic programming
We study nonlinear optimization problems with a stochastic objective and deterministic equality and inequality constraints, which emerge in numerous...
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Service-oriented operational decision optimization for dry bulk ship** fleet under stochastic demand
Dry bulk ship** plays a crucial role in intercontinental bulk cargo transport, with operators managing fleets to meet shippers’ transportation...
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Stochastic optimization problems with nonlinear dependence on a probability measure via the Wasserstein metric
Nonlinear dependence on a probability measure has recently been encountered with increasing intensity in stochastic optimization. This type of...
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Accelerating stochastic sequential quadratic programming for equality constrained optimization using predictive variance reduction
In this paper, we propose a stochastic method for solving equality constrained optimization problems that utilizes predictive variance reduction....
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Nonasymptotic Estimates for Stochastic Gradient Langevin Dynamics Under Local Conditions in Nonconvex Optimization
In this paper, we are concerned with a non-asymptotic analysis of sampling algorithms used in nonconvex optimization. In particular, we obtain...
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Convergence of a Weighted Barrier Algorithm for Stochastic Convex Quadratic Semidefinite Optimization
Mehrotra and Özevin (SIAM J Optim 19:1846–1880, 2009) computationally found that a weighted barrier decomposition algorithm for two-stage stochastic...
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Stochastic Analysis, Filtering, and Stochastic Optimization A Commemorative Volume to Honor Mark H. A. Davis's Contributions
This volume is a collection of research works to honor the late Professor Mark H.A. Davis, whose pioneering work in the areas of Stochastic...
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Optimization of Stochastic Jump Diffusion Systems Nonlinear in the Control
AbstractWe consider the optimal program control problem for a stochastic state- and control-nonlinear jump diffusion system with a given performance...
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Distributed stochastic gradient tracking methods with momentum acceleration for non-convex optimization
We consider a distributed non-convex optimization problem of minimizing the sum of all local cost functions over a network of agents. This problem...
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A three-stage stochastic optimization model integrating 5G technology and UAVs for disaster management
In this paper, we develop a three-stage stochastic network-based optimization model for the provision of 5G services with Unmanned Aerial Vehicles...
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Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization
Many real-world problems not only have complicated nonconvex functional constraints but also use a large number of data points. This motivates the...
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Gradient-free Federated Learning Methods with l1 and l2-randomization for Non-smooth Convex Stochastic Optimization Problems
AbstractThis paper studies non-smooth problems of convex stochastic optimization. Using the smoothing technique based on the replacement of the...
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Momentum-Based Variance-Reduced Proximal Stochastic Gradient Method for Composite Nonconvex Stochastic Optimization
Stochastic gradient methods (SGMs) have been extensively used for solving stochastic problems or large-scale machine learning problems. Recent works...
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Generation of C-NOT, SWAP, and C-Z Gates for Two Qubits Using Coherent and Incoherent Controls and Stochastic Optimization
AbstractIn this work, we consider a general form of the dynamics of open quantum systems determined by the Gorini–Kossakowsky–Sudarchhan–Lindblad...
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Decision bounding problems for two-stage distributionally robust stochastic bilevel optimization
Distributionally robust optimization (DRO) becomes a hot research topic in stochastic programming (SP) due to its characteristic for solving SP...
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Stochastic saddle-point optimization for the Wasserstein barycenter problem
We consider the population Wasserstein barycenter problem for random probability measures supported on a finite set of points and generated by an...
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Stochastic Adversarial Noise in the “Black Box” Optimization Problem
This paper is devoted to the study of the solution of a stochastic convex black box optimization problem. Where the black box problem means that the...