32 citations · 52 across the 20 of their papers we have counts for
3 papers · 1 filter
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers
Liam Hodgkinson, Umut Şimşekli, Rajiv Khanna +1
Despite the ubiquitous use of stochastic optimization algorithms in machine learning, the precise impact of these algorithms and their dynamics on generalization performance in rea…
Taxonomizing local versus global structure in neural network loss landscapes
Yaoqing Yang, Liam Hodgkinson, Ryan Theisen +4
Viewing neural network models in terms of their loss landscapes has a long history in the statistical mechanics approach to learning, and in recent years it has received attention…
Stateful ODE-Nets using Basis Function Expansions
Alejandro Queiruga, N. Benjamin Erichson, Liam Hodgkinson +1
The recently-introduced class of ordinary differential equation networks (ODE-Nets) establishes a fruitful connection between deep learning and dynamical systems. In this work, we…