4 citations · 8 across the 8 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
cs.LG2022★ 2 cited
Gradient Descent for Low-Rank Functions
Romain Cosson, Ali Jadbabaie, Anuran Makur +2
Several recent empirical studies demonstrate that important machine learning tasks, e.g., training deep neural networks, exhibit low-rank structure, where the loss function varies…
stat.ML2022★ 1 cited
Universal Online Learning with Unbounded Losses: Memory Is All You Need
Moise Blanchard, Romain Cosson, Steve Hanneke
We resolve an open problem of Hanneke on the subject of universally consistent online learning with non-i.i.d. processes and unbounded losses. The notion of an optimistically unive…