122 citations · 141 across the 3 of their papers we have counts for
3 papers
cs.LG2016★ 122 cited
Satisfying Real-world Goals with Dataset Constraints
Gabriel Goh, Andrew Cotter, Maya Gupta +1
The goal of minimizing misclassification error on a training set is often just one of several real-world goals that might be defined on different datasets. For example, one may req…
math.OC2016★ 14 cited
Efficient evaluation of scaled proximal operators
Michael P. Friedlander, Gabriel Goh
Quadratic-support functions [Aravkin, Burke, and Pillonetto; J. Mach. Learn. Res. 14(1), 2013] constitute a parametric family of convex functions that includes a range of useful re…
math.OC2013★ 5 cited
Tail bounds for stochastic approximation
Michael P. Friedlander, Gabriel Goh
Stochastic-approximation gradient methods are attractive for large-scale convex optimization because they offer inexpensive iterations. They are especially popular in data-fitting…