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cs.IT2024
Finite Blocklength Performance of Capacity-achieving Codes in the Light of Complexity Theory
Holger Boche, Andrea Grigorescu, Rafael F. Schaefer +1
Since the work of Polyanskiy, Poor and Verdú on the finite blocklength performance of capacity-achieving codes for discrete memoryless channels, many papers have attempted to find…
cs.LG2024
SignSGD with Federated Voting
Chanho Park, H. Vincent Poor, Namyoon Lee
Distributed learning is commonly used for accelerating model training by harnessing the computational capabilities of multiple-edge devices. However, in practical applications, the…