110 citations · 185 across the 21 of their papers we have counts for
4 papers · 1 filter
A constrained optimization approach to improve robustness of neural networks
Shudian Zhao, Jan Kronqvist
In this paper, we present a novel nonlinear programming-based approach to fine-tune pre-trained neural networks to improve robustness against adversarial attacks while maintaining…
A GPU-Accelerated Bi-linear ADMM Algorithm for Distributed Sparse Machine Learning
Alireza Olama, Andreas Lundell, Jan Kronqvist +2
This paper introduces the Bi-linear consensus Alternating Direction Method of Multipliers (Bi-cADMM), aimed at solving large-scale regularized Sparse Machine Learning (SML) problem…
A cutting plane algorithm for globally solving low dimensional k-means clustering problems
Martin Ryner, Jan Kronqvist, Johan Karlsson
Clustering is one of the most fundamental tools in data science and machine learning, and k-means clustering is one of the most common such methods. There is a variety of approxima…
Solution Polishing via Path Relinking for Continuous Black-Box Optimization
Dimitri Papageorgiou, Jan Kronqvist, Asha Ramanujam +3
When faced with a limited budget of function evaluations, state-of-the-art black-box optimization (BBO) solvers struggle to obtain globally, or sometimes even locally, optimal solu…