287 citations · 1.1k across the 60 of their papers we have counts for
4 papers · 1 filter
Slicing Mutual Information Generalization Bounds for Neural Networks
Kimia Nadjahi, Kristjan Greenewald, Rickard Brüel Gabrielsson +1
The ability of machine learning (ML) algorithms to generalize well to unseen data has been studied through the lens of information theory, by bounding the generalization error with…
Sampling with Mollified Interaction Energy Descent
Lingxiao Li, Qiang Liu, Anna Korba +2
Sampling from a target measure whose density is only known up to a normalization constant is a fundamental problem in computational statistics and machine learning. In this paper,…
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
Tal Shnitzer, Mikhail Yurochkin, Kristjan Greenewald +1
The need for efficiently comparing and representing datasets with unknown alignment spans various fields, from model analysis and comparison in machine learning to trend discovery…
Wasserstein Measure Coresets
Sebastian Claici, Aude Genevay, Justin Solomon
The proliferation of large data sets and Bayesian inference techniques motivates demand for better data sparsification. Coresets provide a principled way of summarizing a large dat…