3 papers
math.OC2025
A Regression-Based Prediction-Correction Method for Stochastic Time-Varying Optimization Problems
Tomoya Kamijima, Naoki Marumo, Akiko Takeda
In many real-world applications, optimization problems evolve continuously over time and are often subject to stochastic noise. We consider a stochastic time-varying optimization p…
math.OC2025
A Simple yet Highly Accurate Prediction-Correction Algorithm for Time-Varying Optimization
Tomoya Kamijima, Naoki Marumo, Akiko Takeda
This paper proposes a simple yet highly accurate prediction-correction algorithm, SHARP, for unconstrained time-varying optimization problems. Its prediction is based on an extrapo…
math.OC2024
Contaminated Online Convex Optimization
Tomoya Kamijima, Shinji Ito
In online convex optimization, some efficient algorithms have been designed for each of the individual classes of objective functions, e.g., convex, strongly convex, and exp-concav…