1 citations · 1 across the 15 of their papers we have counts for
19 papers
Differentiating Minimal-Norm Solutions to Parametric Optimization Problems
Baptiste Plaquevent-Jourdain, Jalal Fadili, Antonio Silveti-Falls
Differentiating through parametric optimization problems is central to bilevel programming and meta-learning, often accomplished using approximate implicit differentiation. The imp…
Second order splitting dynamics for stochastic monotone inclusions with closed loop distribution
Wutao Si, Hamza Ennaji, Jalal Fadili
In this paper, we investigate the problem of finding a zero of the sum of a maximal monotone operator and a cocoercive operator $\Bm$ in a Hilbert space. This formulation natur…
The Iterates of Nesterov's Accelerated Algorithm Converge in The Critical Regimes
Radu Ioan Bot, Jalal Fadili, Dang-Khoa Nguyen
In this paper, we prove that the iterates of the accelerated Nesterov's algorithm in the critical regime do converge in the weak topology to a global minimizer of an -smooth fun…
Inexact and Stochastic Gradient Optimization Algorithms with Inertia and Hessian Driven Damping
Harsh Choudhary, Jalal Fadili, Vyachelav Kungurtsev
In a real Hilbert space setting, we study the convergence properties of an inexact gradient algorithm featuring both viscous and Hessian driven damping for convex differentiable op…
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…
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…