Dilated Convolution for Time Series Learning
Wang Zhang, Subhro Das, et al.
ICASSP 2025
We present a distributed protocol for achieving totally unbiased global coin flipping in the presence of an adversary. We consider a synchronous system of n processors at most of which may be corrupted and manipulated by a malicious adversary, and assume a complete network where every two processors are connected via a private channel. Our protocol is deterministic and assumes a very powerful adversary. Although the adversary cannot eavesdrop, it is computationally unbounded, capable of rushing and dynamic. This is the same model that is adopted in Yao's global coin flipping protocol, which we use as the base of our protocol. Our protocol tolerates almost n/3 processor failures and terminates in t + 4 rounds. The resilience of our protocol is greatly improved from that of Yao's protocol at the slight expense of running time, which is only added just two rounds.
Wang Zhang, Subhro Das, et al.
ICASSP 2025
Dzung Phan, Vinicius Lima
INFORMS 2023
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
Albert Atserias, Anuj Dawar, et al.
Journal of the ACM