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. Specifically, we develop a method …
problems that utilizes predictive variance reduction. Specifically, we develop a method …
Nonparametric multi-product dynamic pricing with demand learning via simultaneous price perturbation
We consider the problem of multi-product dynamic pricing with demand learning and
propose a nonparametric online learning algorithm based on the simultaneous perturbation …
propose a nonparametric online learning algorithm based on the simultaneous perturbation …
[PDF][PDF] A First-Order Gradient Approach for the Connectivity Analysis of Markov Chains
CPC Franssen, A Zocca… - arXiv preprint arXiv …, 2024 - alessandrozocca.github.io
Weighted graphs are commonly used to model various complex systems, including social
networks, power grids, transportation networks, and biological systems. In many …
networks, power grids, transportation networks, and biological systems. In many …
Modified Line Search Sequential Quadratic Methods for Equality-Constrained Optimization with Unified Global and Local Convergence Guarantees
In this paper, we propose a method that has foundations in the line search sequential
quadratic programming paradigm for solving general nonlinear equality constrained …
quadratic programming paradigm for solving general nonlinear equality constrained …
Difference Between Cyclic and Distributed Approach in Stochastic Optimization for Multi-agent System
Many stochastic optimization problems in multi-agent systems can be decomposed into
smaller subproblems or reduced decision subspaces. The cyclic and distributed approaches …
smaller subproblems or reduced decision subspaces. The cyclic and distributed approaches …
A First-Order Gradient Approach for the Connectivity Analysis of Weighted Graphs
Weighted graphs are commonly used to model various complex systems, including social
networks, power grids, transportation networks, and biological systems. In many …
networks, power grids, transportation networks, and biological systems. In many …
Switch Updating in SPSA Algorithm for Stochastic Optimization with Inequality Constraints
Simultaneous perturbation stochastic approximation (SPSA) is widely used in stochastic
optimization due to its high efficiency, asymptotic stability, and reduced number of required …
optimization due to its high efficiency, asymptotic stability, and reduced number of required …
SPSA-Based Switch Updating Algorithm for Constrained Stochastic Optimization
Z Jia, Z Wei - 2023 57th Annual Conference on Information …, 2023 - ieeexplore.ieee.org
Simultaneous perturbation stochastic approximation (SPSA) is widely used in stochastic
optimization due to its high efficiency, asymptotic stability, and reduced number of required …
optimization due to its high efficiency, asymptotic stability, and reduced number of required …