A Frank–Wolfe Progressive Hedging Algorithm for Improved Lower Bounds in Stochastic SCUC
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2927346
Abstract: The instantaneous penetration of renewable generation, such as wind and solar generation, reaches over 50% in certain balancing areas in the United States. These generation resources are inherently characterized by uncertainties and variabilities in their… read more here.
Keywords: pha; generation; hedging algorithm; progressive hedging ... See more keywords
Distributed Momentum-Based Frank-Wolfe Algorithm for Stochastic Optimization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2022.105923
Abstract: This paper considers distributed stochastic optimization, in which a number of agents cooperate to optimize a global objective function through local computations and information exchanges with neighbors over a network. Stochastic optimization problems are usually… read more here.
Keywords: momentum based; frank wolfe; stochastic optimization; distributed momentum ... See more keywords
Online Learning for IoT Optimization: A Frank–Wolfe Adam-Based Algorithm
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.2984011
Abstract: Many problems in the Internet of Things (IoT) can be regarded as online optimization problems. For this reason, an online-constrained problem in IoT is considered in this article, where the cost functions change over time.… read more here.
Keywords: tex math; optimization; wolfe adam; inline formula ... See more keywords
Decentralized Randomized Block-Coordinate Frank–Wolfe Algorithms for Submodular Maximization Over Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2021.3112691
Abstract: We consider decentralized large-scale continuous submodular constrained optimization problems over networks, where the goal is to maximize a sum of nonconvex functions with diminishing returns property. However, the computations of the projection step and the… read more here.
Keywords: randomized block; tex math; inline formula; block coordinate ... See more keywords
Randomized Block Frank–Wolfe for Convergent Large-Scale Learning
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2017.2755597
Abstract: Owing to their low-complexity iterations, Frank–Wolfe (FW) solvers are well suited for various large-scale learning tasks. When block-separable constraints are present, randomized block FW (RB-FW) has been shown to further reduce complexity by updating only… read more here.
Keywords: large scale; block; randomized block; frank wolfe ... See more keywords