1.2k citations · 3.4k across the 72 of their papers we have counts for
Showing 2019 · cs.LGShow all
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cs.LG2019★ 133 cited
Differentiable Convex Optimization Layers
Akshay Agrawal, Brandon Amos, Shane Barratt +3
Recent work has shown how to embed differentiable optimization problems (that is, problems whose solutions can be backpropagated through) as layers within deep learning architectur…
cs.LG2019
A General Optimization Framework for Dynamic Time Warping
Dave Deriso, Stephen Boyd
The goal of dynamic time warping is to transform or warp time in order to approximately align two signals together. We pose the choice of warping function as an optimization proble…
cs.LG2019★ 18 cited
A Distributed Method for Fitting Laplacian Regularized Stratified Models
Jonathan Tuck, Shane Barratt, Stephen Boyd
Stratified models are models that depend in an arbitrary way on a set of selected categorical features, and depend linearly on the other features. In a basic and traditional formul…