4 citations · 4 across the 3 of their papers we have counts for
4 papers
A Unified Analysis of Stochastic Gradient Descent with Arbitrary Data Permutations and Beyond
Yipeng Li, Xinchen Lyu, Zhenyu Liu
We aim to provide a unified convergence analysis for permutation-based Stochastic Gradient Descent (SGD), where data examples are permuted before each epoch. By examining the relat…
Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
Yipeng Li, Xinchen Lyu
There are two paradigms in Federated Learning (FL): parallel FL (PFL), where models are trained in a parallel manner across clients, and sequential FL (SFL), where models are train…
Convergence Analysis of Sequential Federated Learning on Heterogeneous Data
Yipeng Li, Xinchen Lyu
There are two categories of methods in Federated Learning (FL) for joint training across multiple clients: (i) parallel FL (PFL), where clients train models in a parallel manner; a…
Convergence Analysis of Sequential Split Learning on Heterogeneous Data
Yipeng Li, Xinchen Lyu
Federated Learning (FL) and Split Learning (SL) are two popular paradigms of distributed machine learning. By offloading the computation-intensive portions to the server, SL is pro…