15 citations · 47 across the 10 of their papers we have counts for
7 papers · 1 filter
Utilizing Redundancy in Cost Functions for Resilience in Distributed Optimization and Learning
Shuo Liu, Nirupam Gupta, Nitin Vaidya
This paper considers the problem of resilient distributed optimization and stochastic machine learning in a server-based architecture. The system comprises a server and multiple ag…
Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy
Nirupam Gupta, Thinh T. Doan, Nitin Vaidya
We consider the problem of Byzantine fault-tolerance in federated machine learning. In this problem, the system comprises multiple agents each with local data, and a trusted centra…
Asynchronous Distributed Optimization with Redundancy in Cost Functions
Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
This paper considers the problem of asynchronous distributed multi-agent optimization on server-based system architecture. In this problem, each agent has a local cost, and the goa…
Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent
Nirupam Gupta, Nitin H. Vaidya
We consider the problem of Byzantine fault-tolerance in the peer-to-peer (P2P) distributed gradient-descent method -- a prominent algorithm for distributed optimization in a P2P sy…
Byzantine Fault-Tolerance in Decentralized Optimization under Minimal Redundancy
Nirupam Gupta, Thinh T. Doan, Nitin H. Vaidya
This paper considers the problem of Byzantine fault-tolerance in multi-agent decentralized optimization. In this problem, each agent has a local cost function. The goal of a decent…
Resilience in Collaborative Optimization: Redundant and Independent Cost Functions
Nirupam Gupta, Nitin H. Vaidya
This report considers the problem of Byzantine fault-tolerance in multi-agent collaborative optimization. In this problem, each agent has a local cost function. The goal of a colla…