1 citations · 1 across the 5 of their papers we have counts for
5 papers
Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks
Zhenghao Xu, Yuqing Wang, Tuo Zhao +2
We study the convergence rate of first-order methods for rectangular matrix factorization, which is a canonical nonconvex optimization problem. Specifically, given a rank- matri…
Robust First and Second-Order Differentiation for Regularized Optimal Transport
Xingjie Li, Fei Lu, Molei Tao +1
Applications such as unbalanced and fully shuffled regression can be approached by optimizing regularized optimal transport (OT) distances, such as the entropic OT and Sinkhorn dis…
Evaluating the design space of diffusion-based generative models
Yuqing Wang, Ye He, Molei Tao
Most existing theoretical investigations of the accuracy of diffusion models, albeit significant, assume the score function has been approximated to a certain accuracy, and then us…
Automated construction of effective potential via algorithmic implicit bias
Xingjie Helen Li, Molei Tao
We introduce a novel approach for decomposing and learning every scale of a given multiscale objective function in , where . This approach leverages a recentl…
Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult
Yuqing Wang, Zhenghao Xu, Tuo Zhao +1
Large learning rates, when applied to gradient descent for nonconvex optimization, yield various implicit biases including the edge of stability (Cohen et al., 2021), balancing (Wa…