30 citations · 79 across the 11 of their papers we have counts for
16 papers
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks
Yunwen Lei, Rong Jin, Yiming Ying
While significant theoretical progress has been achieved, unveiling the generalization mystery of overparameterized neural networks still remains largely elusive. In this paper, we…
Stability and Generalization for Markov Chain Stochastic Gradient Methods
Puyu Wang, Yunwen Lei, Yiming Ying +1
Recently there is a large amount of work devoted to the study of Markov chain stochastic gradient methods (MC-SGMs) which mainly focus on their convergence analysis for solving min…
Stability and Generalization for Randomized Coordinate Descent
Puyu Wang, Liang Wu, Yunwen Lei
Randomized coordinate descent (RCD) is a popular optimization algorithm with wide applications in solving various machine learning problems, which motivates a lot of theoretical an…
Fine-grained Generalization Analysis of Structured Output Prediction
Waleed Mustafa, Yunwen Lei, Antoine Ledent +1
In machine learning we often encounter structured output prediction problems (SOPPs), i.e. problems where the output space admits a rich internal structure. Application domains whe…
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Yunwen Lei, Zhenhuan Yang, Tianbao Yang +1
Many machine learning problems can be formulated as minimax problems such as Generative Adversarial Networks (GANs), AUC maximization and robust estimation, to mention but a few. A…
Fine-grained Generalization Analysis of Vector-valued Learning
Liang Wu, Antoine Ledent, Yunwen Lei +1
Many fundamental machine learning tasks can be formulated as a problem of learning with vector-valued functions, where we learn multiple scalar-valued functions together. Although…