research
∙
09/07/2022
Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps
Convolutional Neural Networks (CNNs) compression is crucial to deploying...
share
research
∙
06/23/2021
Bregman Gradient Policy Optimization
In this paper, we design a novel Bregman gradient policy optimization fr...
research
∙
10/13/2020
Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold
In the paper, we study a class of useful non-convex minimax optimization...
research
∙
08/18/2020
Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization
In the paper, we propose a new accelerated zeroth-order momentum (Acc-ZO...
research
∙
07/13/2020
Momentum-Based Policy Gradient Methods
In the paper, we propose a class of efficient momentum-based policy grad...
research
∙
07/30/2019
Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity
Zeroth-order (gradient-free) method is a class of powerful optimization ...
research
∙
05/29/2019
