354 citations · 1.4k across the 34 of their papers we have counts for
3 papers · 1 filter
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a cen…
Central Server Free Federated Learning over Single-sided Trust Social Networks
Chaoyang He, Conghui Tan, Hanlin Tang +2
Federated learning has become increasingly important for modern machine learning, especially for data privacy-sensitive scenarios. Existing federated learning mostly adopts the cen…
Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling
Zi Long, Lianzhi Tan, Shengping Zhou +2
Indicators of Compromise (IOCs) are artifacts observed on a network or in an operating system that can be utilized to indicate a computer intrusion and detect cyber-attacks in an e…