3 papers
math.OC2025
Knapsack with compactness: a semidefinite approach
Hubert Villuendas, Mathieu Besançon, Jérôme Malick
The min-knapsack problem with compactness constraints extends the classical knapsack problem, in the case of ordered items, by introducing a restriction ensuring that they cannot b…
math.OC2025
The global convergence time of stochastic gradient descent in non-convex landscapes: Sharp estimates via large deviations
Waïss Azizian, Franck Iutzeler, Jérôme Malick +1
In this paper, we examine the time it takes for stochastic gradient descent (SGD) to reach the global minimum of a general, non-convex loss function. We approach this question thro…
cs.LG2024
: a library for Wasserstein distributionally robust machine learning
Florian Vincent, Waïss Azizian, Franck Iutzeler +1
We present skwdro, a Python library for training robust machine learning models. The library is based on distributionally robust optimization using Wasserstein distances, popular i…