101 citations · 214 across the 17 of their papers we have counts for
3 papers · 1 filter
Interpreting Deep Neural Networks Through Variable Importance
Jonathan Ish-Horowicz, Dana Udwin, Seth Flaxman +2
While the success of deep neural networks (DNNs) is well-established across a variety of domains, our ability to explain and interpret these methods is limited. Unlike previously p…
Bayesian Learning of Kernel Embeddings
Seth Flaxman, Dino Sejdinovic, John P. Cunningham +1
Kernel methods are one of the mainstays of machine learning, but the problem of kernel learning remains challenging, with only a few heuristics and very little theory. This is of p…
Regret Bounds for Opportunistic Channel Access
Sarah Filippi, Olivier Cappé, Aurélien Garivier
We consider the task of opportunistic channel access in a primary system composed of independent Gilbert-Elliot channels where the secondary (or opportunistic) user does not dispos…