228 citations · 868 across the 43 of their papers we have counts for
3 papers · 2 filters
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization
Jun-Kun Wang, Jacob Abernethy, Kfir Y. Levy
We develop an algorithmic framework for solving convex optimization problems using no-regret game dynamics. By converting the problem of minimizing a convex function into an auxili…
Escaping Saddle Points Faster with Stochastic Momentum
Jun-Kun Wang, Chi-Heng Lin, Jacob Abernethy
Stochastic gradient descent (SGD) with stochastic momentum is popular in nonconvex stochastic optimization and particularly for the training of deep neural networks. In standard SG…
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness
Jacob Abernethy, Pranjal Awasthi, Satyen Kale
Alongside the well-publicized accomplishments of deep neural networks there has emerged an apparent bug in their success on tasks such as object recognition: with deep models train…