141 citations · 141 across the 1 of their papers we have counts for
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cs.LG2019
First-Order Preconditioning via Hypergradient Descent
Ted Moskovitz, Rui Wang, Janice Lan +4
Standard gradient descent methods are susceptible to a range of issues that can impede training, such as high correlations and different scaling in parameter space.These difficulti…
cs.LG2019
LCA: Loss Change Allocation for Neural Network Training
Janice Lan, Rosanne Liu, Hattie Zhou +1
Neural networks enjoy widespread use, but many aspects of their training, representation, and operation are poorly understood. In particular, our view into the training process is…
cs.LG2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
Hattie Zhou, Janice Lan, Rosanne Liu +1
The recent "Lottery Ticket Hypothesis" paper by Frankle & Carbin showed that a simple approach to creating sparse networks (keeping the large weights) results in models that are tr…