22 citations · 40 across the 29 of their papers we have counts for
4 papers · 2 filters
How to Attain Communication-Efficient DNN Training? Convert, Compress, Correct
Zhong-Jing Chen, Eduin E. Hernandez, Yu-Chih Huang +1
This paper introduces CO3 -- an algorithm for communication-efficient federated Deep Neural Network (DNN) training. CO3 takes its name from three processing applied which reduce th…
Convert, compress, correct: Three steps toward communication-efficient DNN training
Zhong-Jing Chen, Eduin E. Hernandez, Yu-Chih Huang +1
In this paper, we introduce a novel algorithm, , for communication-efficiency distributed Deep Neural Network (DNN) training. is a joint training/com…
Empirical Risk Minimization with Relative Entropy Regularization: Optimality and Sensitivity Analysis
Samir M. Perlaza, Gaetan Bisson, Iñaki Esnaola +2
The optimality and sensitivity of the empirical risk minimization problem with relative entropy regularization (ERM-RER) are investigated for the case in which the reference is a s…
Lossy Gradient Compression: How Much Accuracy Can One Bit Buy?
Sadaf Salehkalaibar, Stefano Rini
In federated learning (FL), a global model is trained at a Parameter Server (PS) by aggregating model updates obtained from multiple remote learners. Generally, the communication b…