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math.OC2025

Convergence rates of regularized quasi-Newton methods without strong convexity

Shida Wang, Jalal Fadili, Peter Ochs

In this paper, we study convergence rates of the cubic regularized proximal quasi-Newton method (\csr) for solving non-smooth additive composite problems that satisfy the so-called…

math.OC2025

Inertial Methods with Viscous and Hessian driven Damping for Non-Convex Optimization

Rodrigo Maulen-Soto, Jalal Fadili, Peter Ochs

In this paper, we aim to study non-convex minimization problems via second-order (in-time) dynamics, including a non-vanishing viscous damping and a geometric Hessian-driven dampin…

math.OC2025

An SDE Perspective on Stochastic Inertial Gradient Dynamics with Time-Dependent Viscosity and Geometric Damping

Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch +1

Our approach is part of the close link between continuous dissipative dynamical systems and optimization algorithms. We aim to solve convex minimization problems by means of stocha…

math.OC2025

Stochastic Inertial Dynamics Via Time Scaling and Averaging

Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch +1

Our work is part of the close link between continuous-time dissipative dynamical systems and optimization algorithms, and more precisely here, in the stochastic setting. We aim to…

math.OC2024

Global non-asymptotic super-linear convergence rates of regularized proximal quasi-Newton methods on non-smooth composite problems

Shida Wang, Jalal Fadili, Peter Ochs

In this paper, we propose two regularized proximal quasi-Newton methods with symmetric rank-1 update of the metric (SR1 quasi-Newton) to solve non-smooth convex additive composite…