11 citations · 24 across the 10 of their papers we have counts for
5 papers · 1 filter
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression
Xiaoyun Li, Ping Li
In federated learning (FL) systems, e.g., wireless networks, the communication cost between the clients and the central server can often be a bottleneck. To reduce the communicatio…
On Distributed Adaptive Optimization with Gradient Compression
Xiaoyun Li, Belhal Karimi, Ping Li
We study COMP-AMS, a distributed optimization framework based on gradient averaging and adaptive AMSGrad algorithm. Gradient compression with error feedback is applied to reduce th…
C-MinHash: Rigorously Reducing Permutations to Two
Xiaoyun Li, Ping Li
Minwise hashing (MinHash) is an important and practical algorithm for generating random hashes to approximate the Jaccard (resemblance) similarity in massive binary (0/1) data. The…
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching
Farzin Haddadpour, Belhal Karimi, Ping Li +1
Communication complexity and privacy are the two key challenges in Federated Learning where the goal is to perform a distributed learning through a large volume of devices. In this…
An Optimistic Acceleration of AMSGrad for Nonconvex Optimization
Jun-Kun Wang, Xiaoyun Li, Belhal Karimi +1
We propose a new variant of AMSGrad, a popular adaptive gradient based optimization algorithm widely used for training deep neural networks. Our algorithm adds prior knowledge abou…