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[HTML][HTML] Optimization algorithms as robust feedback controllers
Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …
practice. Yet, throughout all application domains, mathematical optimization is, for the most …
Running primal-dual gradient method for time-varying nonconvex problems
This paper focuses on a time-varying constrained nonconvex optimization problem, and
considers the synthesis and analysis of online regularized primal-dual gradient methods to …
considers the synthesis and analysis of online regularized primal-dual gradient methods to …
Dynamic Regret Bounds for Constrained Online Nonconvex Optimization Based on Polyak–Lojasiewicz Regions
Online optimization problems are well understood in the convex case, where algorithmic
performance is typically measured relative to the best fixed decision. In this article, we shed …
performance is typically measured relative to the best fixed decision. In this article, we shed …
Co-Optimization of Environment and Policies for Decentralized Multi-Agent Navigation
First-order dynamic optimization for streaming convex costs
This paper proposes a set of novel optimization algorithms for solving a class of convex
optimization problems with time-varying streaming cost functions. We develop an approach …
optimization problems with time-varying streaming cost functions. We develop an approach …
Diminishing regret for online nonconvex optimization
A single nonconvex optimization is NP-hard in the worst case, and so is a sequence of
nonconvex problems viewed separately. For online nonconvex optimization (ONO) …
nonconvex problems viewed separately. For online nonconvex optimization (ONO) …
Time-Varying Convex Optimization with Computational Complexity
In this article, we consider the problem of unconstrained time-varying convex optimization,
where the cost function changes with time. We provide an in-depth technical analysis of the …
where the cost function changes with time. We provide an in-depth technical analysis of the …
[KNJIGA][B] Online, time-varying and multi-period optimization with applications in electric power systems
J Mulvaney-Kemp - 2022 - search.proquest.com
Decision-makers often face environments which vary over time and deal with uncertainty as
a result. Problems with temporal variation differ based on how frequently they are solved …
a result. Problems with temporal variation differ based on how frequently they are solved …
Learning to Forget Advanced Online Recursive Identification for Estimation and Adaptive Control
A Bruce - 2022 - deepblue.lib.umich.edu
In adaptive control and online parameter estimation, recursive identification algorithms, such
as Recursive Least Squares (RLS) or gradient methods, are often used to learn system …
as Recursive Least Squares (RLS) or gradient methods, are often used to learn system …