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cs.LG2026
Pairwise Learning Increases Data Efficiency in Deep Neural Networks
Robert Bain, Marjan Rashidi, Elizabeth Chrastil
Deep neural networks often fail at small-sample regression, collapsing to low-variance predictions that miss individual differences. Here, we introduce a pairwise comparison framew…
cs.LG2021★ 2 cited
Visualizing the Loss Landscape of Winning Lottery Tickets
Robert Bain
The underlying loss landscapes of deep neural networks have a great impact on their training, but they have mainly been studied theoretically due to computational constraints. This…
cs.LG2021
LossPlot: A Better Way to Visualize Loss Landscapes
Robert Bain, Mikhail Tokarev, Harsh Kothari +1
Investigations into the loss landscapes of deep neural networks are often laborious. This work documents our user-driven approach to create a platform for semi-automating this proc…