140 citations · 158 across the 4 of their papers we have counts for
4 papers
Learning with Shared Representations: Statistical Rates and Efficient Algorithms
Xiaochun Niu, Lili Su, Jiaming Xu +1
Collaborative learning through latent shared feature representations enables heterogeneous clients to train personalized models with improved performance and reduced sample complex…
A Non-parametric View of FedAvg and FedProx: Beyond Stationary Points
Lili Su, Jiaming Xu, Pengkun Yang
Federated Learning (FL) is a promising decentralized learning framework and has great potentials in privacy preservation and in lowering the computation load at the cloud. Recent w…
Securing Distributed Gradient Descent in High Dimensional Statistical Learning
Lili Su, Jiaming Xu
We consider unreliable distributed learning systems wherein the training data is kept confidential by external workers, and the learner has to interact closely with those workers t…
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Yudong Chen, Lili Su, Jiaming Xu
We consider the problem of distributed statistical machine learning in adversarial settings, where some unknown and time-varying subset of working machines may be compromised and b…