4 papers
Decentralized Learning via Random Walk with Jumps
Zonghong Liu, Matthew Dwyer, Salim El Rouayheb
We study decentralized learning over networks where data are distributed across nodes without a central coordinator. Random walk learning is a token-based approach in which a singl…
Perfect Privacy and Strong Stationary Times for Markovian Sources
Fangwei Ye, Zonghong Liu, Parimal Parag +1
We consider the problem of sharing correlated data under a perfect information-theoretic privacy constraint. We focus on redaction (erasure) mechanisms, in which data are either wi…
Random Walk Learning and the Pac-Man Attack
Xingran Chen, Parimal Parag, Rohit Bhagat +2
Random walk (RW)-based algorithms have long been popular in distributed systems due to low overheads and scalability, with recent growing applications in decentralized learning. Ho…
The Entrapment Problem in Random Walk Decentralized Learning
Zonghong Liu, Salim El Rouayheb, Matthew Dwyer
This paper explores decentralized learning in a graph-based setting, where data is distributed across nodes. We investigate a decentralized SGD algorithm that utilizes a random wal…