Courses - Fall 2024
CMSC848Z
Selected Topics in Information Processing; Federated Learning
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: ENEE436 or CMSC422; or students who have taken courses with comparable content may contact the Department. Cross-listed with ENEE759Z. Credit only granted for ENEE759Z or CMSC848Z.
Principles and applications of federated learning. Federated optimization, statistical and system homogeneity models, variations of federated aggregation, security and privacy considerations, foundation models.
Principles and applications of federated learning. Federated optimization, statistical and system homogeneity models, variations of federated aggregation, security and privacy considerations, foundation models.
Flagship Institution of the University System of Maryland
University of Maryland, College Park, MD 20742, USA
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301.405.1000
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