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math.OC2025
Temporal Variabilities Limit Convergence Rates in Gradient-Based Online Optimization
Bryan Van Scoy, Gianluca Bianchin
This paper investigates the fundamental performance limits of gradient-based algorithms for time-varying optimization. Leveraging the internal model principle and root locus techni…
math.OC2025
Feedback Optimization of Dynamical Systems in Time-Varying Environments: An Internal Model Principle Approach
Gianluca Bianchin, Bryan Van Scoy
Feedback optimization has emerged as a promising approach for regulating dynamical systems to optimal steady states that are implicitly defined by underlying optimization problems.…
math.OC2025
The Fastest Known First-Order Method for Minimizing Twice Continuously Differentiable Smooth Strongly Convex Functions
Bryan Van Scoy, Laurent Lessard
We consider iterative gradient-based optimization algorithms applied to functions that are smooth and strongly convex. The fastest globally convergent algorithm for this class of f…