MicroFedML: Privacy Preserving Federated Learning for Small Weights

Explore a conference talk from PPML 2022 Contributed Talks I focusing on MicroFedML, a novel approach to privacy-preserving federated learning designed for small weights. Gain insights into cutting-edge techniques for maintaining data privacy in machine learning applications, particularly in resource-constrained environments. Discover how this innovative method addresses challenges in federated learning while ensuring confidentiality and efficiency.

PPML 2022 Contributed Talks I (part II)