12 papers
Active learning-based Bayesian optimization in the realm of copper slag-blended cement systems
Debadri Som, Rayna Maheshwari, Mathijs Schuurmans +2
Accelerated mix design optimization is critical for deploying low-carbon supplementary cementitious materials (SCMs) because traditional experimental approaches require extensive t…
A Lasry-Lions envelope approach for mathematical programs with complementarity constraints
Jia Wang, Andreas Themelis, Ivan Markovsky +1
We propose a homotopy method for solving mathematical programs with complementarity constraints (CCs). The indicator function of the CCs is relaxed by the Lasry--Lions double envel…
Newton methods beyond Hessian Lipschitz continuity: A nonlinear preconditioning approach
Alexander Bodard, Panagiotis Patrinos
Newton-type methods are typically analyzed under Lipschitz continuity of the Hessian, an assumption that can fail for objectives with higher-order or polynomial growth. We introduc…
Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
Konstantinos Oikonomidis, Jan Quan, Kimon Antonakopoulos +3
In this work, we develop proximal preconditioned gradient methods with a focus on spectral gradient methods providing a proximal extension to the Muon and Scion optimizers. We intr…
Nonlinearly preconditioned gradient flows
Konstantinos Oikonomidis, Alexander Bodard, Jan Quan +1
We study a continuous-time dynamical system which arises as the limit of a broad class of nonlinearly preconditioned gradient methods. Under mild assumptions, we establish existenc…
PANOC-lite: A simpler and more efficient algorithm for composite minimization
Alexander Bodard, Pieter Pas, Andreas Themelis +1
This work introduces a simple and efficient linesearch method for composite minimization that accelerates proximal-gradient iterations with fast Newton-type directions. Our algorit…