Optimization

Advancing Model Pruning via Bi-level Optimization

Redeeming Intrinsic Rewards via Constrained Optimization

Higher-Order Certification For Randomized Smoothing

Training Stronger Baselines for Learning to Optimize

Why Gradient Clipping accelerates training for neural networks

Implementation Matters in Deep RL: A Case Study on PPO and TRPO

A Closer Look at Deep Policy Gradients

Deep Symbolic Superoptimization Without Human Knowledge

On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization

Automating machine learning with a joint selection framework

ZO-AdaMM: Derivative-free optimization for black-box problems

signSGD via Zeroth-Order Oracle

AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization