no code implementations • ICLR 2022 • Vien V. Mai, Jacob Lindbäck, Mikael Johansson
In addition, we establish a linear convergence rate for our formulation of the OT problem.
no code implementations • 12 Feb 2021 • Vien V. Mai, Mikael Johansson
We also study the convergence of a clipped method with momentum, which includes clipped SGD as a special case, for weakly convex problems under standard assumptions.
no code implementations • ICML 2020 • Vien V. Mai, Mikael Johansson
This paper establishes the convergence rate of a stochastic subgradient method with a momentum term of Polyak type for a broad class of non-smooth, non-convex, and constrained optimization problems.
1 code implementation • ICML 2020 • Vien V. Mai, Mikael Johansson
We therefore propose a simple scheme for stabilization that combines the global worst-case guarantees of proximal gradient methods with the local adaptation and practical speed-up of Anderson acceleration.
no code implementations • 20 Mar 2019 • Vien V. Mai, Mikael Johansson
This paper introduces an efficient algorithm for finding the dominant generalized eigenvectors of a pair of symmetric matrices.
no code implementations • 24 Jan 2019 • Vien V. Mai, Mikael Johansson
This paper introduces an efficient second-order method for solving the elastic net problem.
