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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 decentralized optimization algorithm is to allow the agents to…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-01 Nirupam Gupta , Thinh T. Doan , 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 collaborative optimization algorithm is to compute a minimum of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-04-01 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 system. In this problem, the system comprises of multiple…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-01 Nirupam Gupta , Nitin H. 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 centralized coordinator. In fault-free setting, the agents…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-27 Nirupam Gupta , Thinh T. Doan , Nitin Vaidya

This paper considers the problem of Byzantine fault tolerance in distributed linear regression in a multi-agent system. However, the proposed algorithms are given for a more general class of distributed optimization problems, of which…

Machine Learning · Computer Science 2019-04-05 Nirupam Gupta , Nitin H. Vaidya

We study fault-tolerant distributed optimization of a sum of convex (cost) functions with real-valued scalar input/output in the presence of crash faults or Byzantine faults. In particular, the goal is to optimize a global cost function…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-09-08 Lili Su , Nitin Vaidya

We study Byzantine fault-tolerant distributed optimization of a sum of convex (cost) functions with real-valued scalar input/ouput. In particular, the goal is to optimize a global cost function $\frac{1}{|\mathcal{N}|}\sum_{i\in…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-03 Lili Su , 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 agents, where each agent has a local cost function. The agents…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-22 Shuo Liu , Nirupam Gupta , Nitin Vaidya

This paper studies the distributed multi-agent resilient optimization problem under the f-total Byzantine attacks. Compared with the previous work on Byzantineresilient multi-agent exact optimization problems, we do not require the…

Optimization and Control · Mathematics 2023-03-29 Yang Zhai , Zhi-Wei Liu , Dong Yue , Songlin Hu , Xiangpeng Xie

In this report, we study the problem of Byzantine fault-tolerant distributed set intersection and the importance of redundancy in solving this problem. Specifically, consider a distributed system with $n$ agents, each of which has a local…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-15 Shuo Liu , Nitin H. Vaidya

In this paper, we consider a min-max optimization problem under adversarial manipulation, where there are $n$ cost functions, up to $f$ of which may be replaced by arbitrary faulty functions by an adversary. The goal is to minimize the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-19 Shuo Liu , Nitin Vaidya

We study the problem of Byzantine fault tolerance in a distributed optimization setting, where there is a group of $N$ agents communicating with a trusted centralized coordinator. Among these agents, there is a subset of $f$ agents that may…

Optimization and Control · Mathematics 2023-12-19 Amit Dutta , Thinh T. Doan , Jeffrey H. Reed

This report considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-15 Shuo Liu , Nirupam Gupta , Nitin H. Vaidya

The problem of distributed optimization requires a group of agents to reach agreement on a parameter that minimizes the average of their local cost functions using information received from their neighbors. While there are a variety of…

Optimization and Control · Mathematics 2024-03-05 Kananart Kuwaranancharoen , Lei Xin , Shreyas Sundaram

In Part I of this report, we introduced a Byzantine fault-tolerant distributed optimization problem whose goal is to optimize a sum of convex (cost) functions with real-valued scalar input/ouput. In this second part, we introduce a…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-08 Lili Su , Nitin Vaidya

This work considers resilient, cooperative state estimation in unreliable multi-agent networks. A network of agents aims to collaboratively estimate the value of an unknown vector parameter, while an {\em unknown} subset of agents suffer…

Systems and Control · Computer Science 2018-10-25 Lili Su , Shahin Shahrampour

We study the problem of constrained distributed optimization in multi-agent networks when some of the computing agents may be faulty. In this problem, the system goal is to have all the non-faulty agents collectively minimize a global…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-06 Lili Su , Nitin H. Vaidya

The problem of distributed optimization requires a group of networked agents to compute a parameter that minimizes the average of their local cost functions. While there are a variety of distributed optimization algorithms that can solve…

Multiagent Systems · Computer Science 2024-09-24 Kananart Kuwaranancharoen , Lei Xin , Shreyas Sundaram

This paper considers a distributed optimization problem in the presence of Byzantine agents capable of introducing untrustworthy information into the communication network. A resilient distributed subgradient algorithm is proposed based on…

Optimization and Control · Mathematics 2023-03-22 Jingxuan Zhu , Yixuan Lin , Alvaro Velasquez , Ji Liu

The problem of designing distributed optimization algorithms that are resilient to Byzantine adversaries has received significant attention. For the Byzantine-resilient distributed optimization problem, the goal is to (approximately)…

Optimization and Control · Mathematics 2024-12-30 Kananart Kuwaranancharoen , Shreyas Sundaram
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