research
∙
05/08/2023
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data
Decentralized learning enables the training of deep learning models over...
share
research
∙
04/09/2023
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
Decentralized learning enables serverless training of deep neural networ...
research
∙
03/27/2023
CoDeC: Communication-Efficient Decentralized Continual Learning
Training at the edge utilizes continuously evolving data generated at di...
research
∙
09/28/2022
Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions
Decentralized learning over distributed datasets can have significantly ...
research
∙
11/17/2021
Low Precision Decentralized Distributed Training over IID and non-IID Data
Decentralized distributed learning is the key to enabling large-scale ma...
research
∙
02/10/2021
Sparse-Push: Communication- Energy-Efficient Decentralized Distributed Learning over Directed Time-Varying Graphs with non-IID Datasets
Current deep learning (DL) systems rely on a centralized computing parad...
research
∙
02/25/2020
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors
Deep neural networks have demonstrated state-of-the-art performance on m...
research
∙
02/23/2020
Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks
The enormous inference cost of deep neural networks can be scaled down b...
research
∙
01/13/2020
