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We study adversary-resilient stochastic distributed optimization, in which $m$ machines can independently compute stochastic gradients, and cooperate to jointly optimize over their local objective functions. However, an $\alpha$-fraction of…

Machine Learning · Computer Science 2021-04-05 Zeyuan Allen-Zhu , Faeze Ebrahimian , Jerry Li , Dan Alistarh

It is a common belief that Byzantine fault-tolerant solutions for consensus are significantly slower than their crash fault-tolerant counterparts. Indeed, in PBFT, the most widely known Byzantine fault-tolerant consensus protocol, it takes…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-28 Petr Kuznetsov , Andrei Tonkikh , Yan X Zhang

We study robust distributed learning that involves minimizing a non-convex loss function with saddle points. We consider the Byzantine setting where some worker machines have abnormal or even arbitrary and adversarial behavior. In this…

Machine Learning · Computer Science 2020-07-30 Dong Yin , Yudong Chen , Kannan Ramchandran , Peter Bartlett

The Byzantine agreement problem is considered to be a core problem in distributed systems. For example, Byzantine agreement is needed to build a blockchain, a totally ordered log of records. Blockchains are asynchronous distributed systems,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-27 Ye Wang , Roger Wattenhofer

In this paper, we present a Byzantine fault tolerant distributed commit protocol for transactions running over untrusted networks. The traditional two-phase commit protocol is enhanced by replicating the coordinator and by running a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-17 Wenbing Zhao

Blockchain technology offers a decentralized and secure method for storing and authenticating data, rendering it well-suited for various applications such as digital currencies, supply chain management, and voting systems. However, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-25 Mohammad R. Shakournia , Pooya Jamshidi , Hamid Reza Faragardi , Nasser Yazdani

Communication between workers and the master node to collect local stochastic gradients is a key bottleneck in a large-scale federated learning system. Various recent works have proposed to compress the local stochastic gradients to…

Machine Learning · Computer Science 2024-02-06 Heng Zhu , Qing Ling

We propose a novel relaxation of the classic asynchronous network model, called the random asynchronous model, which removes adversarial message scheduling while preserving unbounded message delays and Byzantine faults. Instead of an…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-27 George Danezis , Jovan Komatovic , Lefteris Kokoris-Kogias , Alberto Sonnino , Igor Zablotchi

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

Implementations of SGD on distributed systems create new vulnerabilities, which can be identified and misused by one or more adversarial agents. Recently, it has been shown that well-known Byzantine-resilient gradient aggregation schemes…

Machine Learning · Computer Science 2022-09-26 Ali Ramezani-Kebrya , Iman Tabrizian , Fartash Faghri , Petar Popovski

This paper studies the Byzantine Agreement problem where the nodes have access to a predictor that flags nodes for suspicion of faulty (Byzantine) behavior. We focus on algorithmic resilience -- the maximum number of faulty nodes an…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-20 Julien Dallot , Darya Melnyk , Tijana Milentijevic , Stefan Schmid , Patrik Welters

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence…

Machine Learning · Computer Science 2022-05-25 Sadegh Farhadkhani , Rachid Guerraoui , Nirupam Gupta , Rafael Pinot , John Stephan

Byzantine-robust distributed learning (BRDL), in which computing devices are likely to behave abnormally due to accidental failures or malicious attacks, has recently become a hot research topic. However, even in the independent and…

Machine Learning · Computer Science 2023-05-24 Yi-Rui Yang , Chang-Wei Shi , Wu-Jun Li

Byzantine-robust learning has emerged as a prominent fault-tolerant distributed machine learning framework. However, most techniques focus on the static setting, wherein the identity of Byzantine workers remains unchanged throughout the…

Machine Learning · Computer Science 2024-06-18 Ron Dorfman , Naseem Yehya , Kfir Y. Levy

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

Ensuring that an AI system behaves reliably and as intended, especially in the presence of unexpected faults or adversarial conditions, is a complex challenge. Inspired by the field of Byzantine Fault Tolerance (BFT) from distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-30 John deVadoss , Matthias Artzt

We propose two novel stochastic gradient descent algorithms, ByGARS and ByGARS++, for distributed machine learning in the presence of any number of Byzantine adversaries. In these algorithms, reputation scores of workers are computed using…

Machine Learning · Computer Science 2020-12-09 Jayanth Regatti , Hao Chen , Abhishek Gupta

We consider gradient coding in the presence of an adversary, controlling so-called malicious workers trying to corrupt the computations. Previous works propose the use of MDS codes to treat the inputs of the malicious workers as errors and…

Information Theory · Computer Science 2023-06-06 Christoph Hofmeister , Luis Maßny , Eitan Yaakobi , Rawad Bitar

We consider the problem of fault-tolerant parallel search on an infinite line by $n$ robots. Starting from the origin, the robots are required to find a target at an unknown location. The robots can move with maximum speed $1$ and can…

Data Structures and Algorithms · Computer Science 2016-11-28 Jurek Czyzowicz , Konstantinos Georgiou , Evangelos Kranakis , Danny Krizanc , Lata Narayanan , Jaroslav Opatrny , Sunil Shende

For tolerating Byzantine faults of both the terminal and communication components in self-stabilizing clock synchronization, the two-dimensional self-stabilizing Byzantine-fault-tolerant clock synchronization problem is investigated and…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-08 Shaolin Yu , Jihong Zhu , Jiali Yang
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