66 citations · 72 across the 10 of their papers we have counts for
4 papers · 1 filter
Adaptive Deadline and Batch Layered Synchronized Federated Learning
Asaf Goren, Natalie Lang, Nir Shlezinger +1
Federated learning (FL) enables collaborative model training across distributed edge devices while preserving data privacy, and typically operates in a round-based synchronous mann…
PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning
Ori Peleg, Natalie Lang, Dan Ben Ami +3
Federated learning (FL) enables multiple edge devices to collaboratively train a machine learning model without the need to share potentially private data. Federated learning proce…
Stragglers-Aware Low-Latency Synchronous Federated Learning via Layer-Wise Model Updates
Natalie Lang, Alejandro Cohen, Nir Shlezinger
Synchronous federated learning (FL) is a popular paradigm for collaborative edge learning. It typically involves a set of heterogeneous devices locally training neural network (NN)…
Joint Privacy Enhancement and Quantization in Federated Learning
Natalie Lang, Elad Sofer, Tomer Shaked +1
Federated learning (FL) is an emerging paradigm for training machine learning models using possibly private data available at edge devices. The distributed operation of FL gives ri…