198 citations · 339 across the 18 of their papers we have counts for
4 papers · 1 filter
Kernel Interpolation as a Bayes Point Machine
Jeremy Bernstein, Alex Farhang, Yisong Yue
A Bayes point machine is a single classifier that approximates the majority decision of an ensemble of classifiers. This paper observes that kernel interpolation is a Bayes point m…
Fine-Grained System Identification of Nonlinear Neural Circuits
Dawna Bagherian, James Gornet, Jeremy Bernstein +3
We study the problem of sparse nonlinear model recovery of high dimensional compositional functions. Our study is motivated by emerging opportunities in neuroscience to recover fin…
Computing the Information Content of Trained Neural Networks
Jeremy Bernstein, Yisong Yue
How much information does a learning algorithm extract from the training data and store in a neural network's weights? Too much, and the network would overfit to the training data.…
Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister +1
Descent methods for deep networks are notoriously capricious: they require careful tuning of step size, momentum and weight decay, and which method will work best on a new benchmar…