11 citations · 15 across the 6 of their papers we have counts for
Showing 2020Show all
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stat.ML2020★ 1 cited
Gradient-only line searches to automatically determine learning rates for a variety of stochastic training algorithms
Dominic Kafka, Daniel Nicolas Wilke
Gradient-only and probabilistic line searches have recently reintroduced the ability to adaptively determine learning rates in dynamic mini-batch sub-sampled neural network trainin…
stat.ML2020★ 1 cited
Investigating the interaction between gradient-only line searches and different activation functions
D. Kafka, Daniel. N. Wilke
Gradient-only line searches (GOLS) adaptively determine step sizes along search directions for discontinuous loss functions resulting from dynamic mini-batch sub-sampling in neural…
stat.ML2020
Resolving learning rates adaptively by locating Stochastic Non-Negative Associated Gradient Projection Points using line searches
Dominic Kafka, Daniel N. Wilke
Learning rates in stochastic neural network training are currently determined a priori to training, using expensive manual or automated iterative tuning. This study proposes gradie…