NIPS & Allerton
Two machine-learning papers on which I collaborated with other researchers have been accepted by NIPS 2016 and Allerton 2016, respectively. I was fortunate to be able to help on these papers a little bit from a systems perspective.
NIPS 2016: Xinghao Pan (Berkeley) et al.: CYCLADES: Conflict-free Asynchronous Machine Learning
Allerton 2016: Ioannis and Stefan (Stanford) have had a paper accepted by Allerton 2016. In this paper, Ioannis articulates elegantly the relationship between momentum and asynchrony for distributed stochastic gradient descent. The theoretical result is inspired by Stefan's distributed deep-learning system, called Omnivore, which is described here.