63.6k citations · 64.4k across the 30 of their papers we have counts for
3 papers · 1 filter
Sparsity-Constrained Optimal Transport
Tianlin Liu, Joan Puigcerver, Mathieu Blondel
Regularized optimal transport (OT) is now increasingly used as a loss or as a matching layer in neural networks. Entropy-regularized OT can be computed using the Sinkhorn algorithm…
Learning Energy Networks with Generalized Fenchel-Young Losses
Mathieu Blondel, Felipe Llinares-López, Robert Dadashi +2
Energy-based models, a.k.a. energy networks, perform inference by optimizing an energy function, typically parametrized by a neural network. This allows one to capture potentially…
Cutting Some Slack for SGD with Adaptive Polyak Stepsizes
Robert M. Gower, Mathieu Blondel, Nidham Gazagnadou +1
Tuning the step size of stochastic gradient descent is tedious and error prone. This has motivated the development of methods that automatically adapt the step size using readily a…