7 citations · 16 across the 4 of their papers we have counts for
4 papers
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent
Xiaoge Deng, Li Shen, Shengwei Li +3
Stochastic gradient descent (SGD) performed in an asynchronous manner plays a crucial role in training large-scale machine learning models. However, the generalization performance…
Adaptive and Implicit Regularization for Matrix Completion
Zhemin Li, Tao Sun, Hongxia Wang +1
The explicit low-rank regularization, e.g., nuclear norm regularization, has been widely used in imaging sciences. However, it has been found that implicit regularization outperfor…
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion
Zhemin Li, Tao Sun, Hongxia Wang +1
The explicit low-rank regularization, e.g., nuclear norm regularization, has been widely used in imaging sciences. However, it has been found that implicit regularization outperfor…
Stability and Generalization of the Decentralized Stochastic Gradient Descent
Tao Sun, Dongsheng Li, Bao Wang
The stability and generalization of stochastic gradient-based methods provide valuable insights into understanding the algorithmic performance of machine learning models. As the ma…