4 papers · 1 filter
Practical Regularized Quasi-Newton Methods with Inexact Function Values
Hiroki Hamaguchi, Naoki Marumo, Akiko Takeda
Many practical optimization problems involve objective function values that are corrupted by unavoidable numerical errors. In smooth nonconvex optimization, quasi-Newton methods co…
Complexity and convergence analysis of a single-loop SDCAM for Lipschitz composite optimization and beyond
Hao Zhang, Naoki Marumo, Ting Kei Pong +1
We develop and analyze a single-loop algorithm for minimizing the sum of a Lipschitz differentiable function , a prox-friendly proper closed function (with a closed domain o…
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…
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…