4 citations · 7 across the 6 of their papers we have counts for
3 papers · 1 filter
Stochastic Rounding Implicitly Regularizes Tall-and-Thin Matrices
Gregory Dexter, Christos Boutsikas, Linkai Ma +2
Motivated by the popularity of stochastic rounding in the context of machine learning and the training of large-scale deep neural network models, we consider stochastic nearness ro…
Feature Space Sketching for Logistic Regression
Gregory Dexter, Rajiv Khanna, Jawad Raheel +1
We present novel bounds for coreset construction, feature selection, and dimensionality reduction for logistic regression. All three approaches can be thought of as sketching the l…
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees
Gregory Dexter, Kevin Bello, Jean Honorio
Inverse Reinforcement Learning (IRL) is the problem of finding a reward function which describes observed/known expert behavior. The IRL setting is remarkably useful for automated…