Co-occurring keywords · papers mentioning both
Papers
SGD Can Converge to Local Maxima
ICLR 2022
Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points
ICML 2022
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems
NeurIPS 2022
A first-order primal-dual method with adaptivity to local smoothness
NeurIPS 2021
Byzantine-Resilient Non-Convex Stochastic Gradient Descent
ICLR 2021
Direct-Search for a Class of Stochastic Min-Max Problems
AISTATS 2021
Escape saddle points by a simple gradient-descent based algorithm
NeurIPS 2021
Escaping Saddle Points with Compressed SGD
NeurIPS 2021
Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems
NeurIPS 2021
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks
JMLR 2021
Sample Complexity of Policy Gradient Finding Second-Order Stationary Points
AAAI 2021
The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks
COLT 2021
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
ICLR 2020
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
AISTATS 2020
Coarse Correlation in Extensive-Form Games
AAAI 2020
Escaping Saddle Points Faster with Stochastic Momentum
ICLR 2020
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems
COLT 2020
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems
NeurIPS 2020
Revisiting the Landscape of Matrix Factorization
AISTATS 2020
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking
NeurIPS 2020
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
ICML 2019
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
ICML 2019
Efficient Dictionary Learning with Gradient Descent
ICML 2019
Efficiently avoiding saddle points with zero order methods: No gradients required
NeurIPS 2019
Efficiently escaping saddle points on manifolds
NeurIPS 2019