77 citations · 86 across the 8 of their papers we have counts for
3 papers · 1 filter
Magnitude Invariant Parametrizations Improve Hypernetwork Learning
Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca
Hypernetworks, neural networks that predict the parameters of another neural network, are powerful models that have been successfully used in diverse applications from image genera…
Trade-offs of Local SGD at Scale: An Empirical Study
Jose Javier Gonzalez Ortiz, Jonathan Frankle, Mike Rabbat +2
As datasets and models become increasingly large, distributed training has become a necessary component to allow deep neural networks to train in reasonable amounts of time. Howeve…
What is the State of Neural Network Pruning?
Davis Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle +1
Neural network pruning---the task of reducing the size of a network by removing parameters---has been the subject of a great deal of work in recent years. We provide a meta-analysi…