TH4.R3.1

Sparsity-Based Secure Gradient Aggregation for Resource-Constrained Federated Learning

Hasin Us Sami, Basak Guler, University of California Riverside, United States
Session:
Secure Aggregation in Federated Learning
Track:
15: Distributed and Federated Learning
Location:
Ypsilon IV-V-VI
Presentation Time:
Thu, 11 Jul, 16:25 - 16:45
Session Chair:
Changho Suh, KAIST
Presentation
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Discussion
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Session TH4.R3
TH4.R3.1: Sparsity-Based Secure Gradient Aggregation for Resource-Constrained Federated Learning
Hasin Us Sami, Basak Guler, University of California Riverside, United States
TH4.R3.2: Secure Submodel Aggregation for Resource-Aware Federated Learning
Hasin Us Sami, Basak Guler, University of California Riverside, United States
TH4.R3.3: On the Optimality of Secure Aggregation with Uncoded Groupwise Keys Against User Dropouts and User Collusion
Ziting Zhang, Jiayu Liu, Kai Wan, Huazhong University of Science and Technology, China; Hua Sun, University of North Texas, United States; Mingyue Ji, University of Utah, United States; Giuseppe Caire, Technische Universitat Berlin, Germany
TH4.R3.4: Optimal Information Theoretic Secure Aggregation with Uncoded Groupwise Keys
Kai Wan, Huazhong University of Science and Technology, China; Hua Sun, University of North Texas, United States; Mingyue Ji, University of Utah, United States; Tiebin Mi, Huazhong University of Science and Technology, China; Giuseppe Caire, Technische Universitat Berlin, Germany
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