[HTML][HTML] Trustworthy decentralized collaborative learning for edge intelligence: A survey
Edge intelligence is an emerging technology that enables artificial intelligence on connected
systems and devices in close proximity to the data sources. Decentralized Collaborative …
systems and devices in close proximity to the data sources. Decentralized Collaborative …
Global update tracking: A decentralized learning algorithm for heterogeneous data
Decentralized learning enables the training of deep learning models over large distributed
datasets generated at different locations, without the need for a central server. However, in …
datasets generated at different locations, without the need for a central server. However, in …
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models
Recent advances in decentralized deep learning algorithms have demonstrated cutting-
edge performance on various tasks with large pre-trained models. However a pivotal …
edge performance on various tasks with large pre-trained models. However a pivotal …
Homogenizing non-iid datasets via in-distribution knowledge distillation for decentralized learning
Decentralized learning enables serverless training of deep neural networks (DNNs) in a
distributed manner on multiple nodes. This allows for the use of large datasets, as well as …
distributed manner on multiple nodes. This allows for the use of large datasets, as well as …
Cross-feature Contrastive Loss for Decentralized Deep Learning on Heterogeneous Data
The current state-of-the-art decentralized learning algorithms mostly assume the data
distribution to be Independent and Identically Distributed (IID). However, in practical …
distribution to be Independent and Identically Distributed (IID). However, in practical …