10 citations · 10 across the 1 of their papers we have counts for
2 papers
stat.ML2022★ 10 cited
Understanding the bias-variance tradeoff of Bregman divergences
Ben Adlam, Neha Gupta, Zelda Mariet +1
This paper builds upon the work of Pfau (2013), which generalized the bias variance tradeoff to any Bregman divergence loss function. Pfau (2013) showed that for Bregman divergence…
stat.ML2018
Estimating the Spectral Density of Large Implicit Matrices
Ryan P. Adams, Jeffrey Pennington, Matthew J. Johnson +4
Many important problems are characterized by the eigenvalues of a large matrix. For example, the difficulty of many optimization problems, such as those arising from the fitting of…