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Standard bandit algorithms that assume continual reallocation of measurement effort are challenging to implement due to delayed feedback and infrastructural/organizational difficulties. Motivated by practical instances involving a handful…

Machine Learning · Computer Science 2023-08-16 Ethan Che , Hongseok Namkoong

In this work, we consider a binary classification problem and cast it into a binary hypothesis testing framework, where the observations can be perturbed by an adversary. To improve the adversarial robustness of a classifier, we include an…

Machine Learning · Computer Science 2021-10-01 Abed AlRahman Al Makdah , Vaibhav Katewa , Fabio Pasqualetti

This paper describes a simple and efficient asynchronous Binary Byzantine faulty tolerant consensus algorithm. In the algorithm, non-faulty nodes perform an initial broadcast followed by a executing a series of rounds each consisting of a…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-12 Tyler Crain

A hard-fork reconfiguration of the peer to peer Bitcoin network is described that substitutes tamper-evident logs and proof-of-stake consensus for proof-of-work consensus. The block creation rewards and transaction fees are reallocated to…

Computers and Society · Computer Science 2014-05-23 Stephen L. Reed

We study randomized test-and-set (TAS) implementations from registers in the asynchronous shared memory model with n processes. We introduce the problem of group election, a natural variant of leader election, and propose a framework for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-12 George Giakkoupis , Philipp Woelfel

Robust planning in interactive scenarios requires predicting the uncertain future to make risk-aware decisions. Unfortunately, due to long-tail safety-critical events, the risk is often under-estimated by finite-sampling approximations of…

Machine Learning · Computer Science 2023-01-13 Haruki Nishimura , Jean Mercat , Blake Wulfe , Rowan McAllister , Adrien Gaidon

In recent decades, the RAFT distributed consensus algorithm has become a main pillar of the distributed systems ecosystem, ensuring data consistency and fault tolerance across multiple nodes. Although the fact that RAFT is well known for…

Cryptography and Security · Computer Science 2026-01-05 Tamer Afifi , Abdelfatah Hegazy , Ehab Abousaif

Byzantine fault tolerant protocols enable state replication in the presence of crashed, malfunctioning, or actively malicious processes. Designing such protocols without the assistance of verification tools, however, is remarkably…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-23 Joel Wanner , Laurent Chuat , Adrian Perrig

Electing a leader is a classical problem in distributed computing system. Synchronization between processes often requires one process acting as a coordinator. If an elected leader node fails, the other nodes of the system need to elect…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-14 P Beaulah Soundarabai , Ritesh Sahai , Thriveni J , K R Venugopal , L M Patnaik

Blockchain technologies originate from cryptocurrencies. Thus, most blockchain technologies assume an environment with a fast and stable network. However, in some blockchain-based systems, e.g., supply chain management (SCM) systems, some…

This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by all the authors. Naive versions of conventional resilience…

In reliability engineering, data about failure events is often scarce. To arrive at meaningful estimates for the reliability of a system, it is therefore often necessary to also include expert information in the analysis, which is…

Methodology · Statistics 2016-10-25 Gero Walter , Frank P. A. Coolen

To improve the resilience of distributed training to worst-case, or Byzantine node failures, several recent approaches have replaced gradient averaging with robust aggregation methods. Such techniques can have high computational costs,…

Machine Learning · Computer Science 2020-03-10 Shashank Rajput , Hongyi Wang , Zachary Charles , Dimitris Papailiopoulos

Bayesian optimization is a framework for global search via maximum a posteriori updates rather than simulated annealing, and has gained prominence for decision-making under uncertainty. In this work, we cast Bayesian optimization as a…

Machine Learning · Computer Science 2022-03-24 Amrit Singh Bedi , Dheeraj Peddireddy , Vaneet Aggarwal , Brian M. Sadler , Alec Koppel

We introduce two models of consensus following a majority rule on time-evolving stochastic block models (SBM), in which the network evolution is Markovian or non-Markovian. Under the majority rule, in each round, each agent simultaneously…

Probability · Mathematics 2022-09-12 Haoyu Wang , Jiaheng Wei , Zhenyuan Zhang

In contrast to proof-of-work replication, Byzantine quorum systems maintain consistency across replicas with higher throughput modest energy consumption, and deterministic liveness guarantees. If complemented with heterogeneous trust and…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-26 Xiao Li , Mohsen Lesani

The recent surge of blockchain systems has renewed the interest in traditional Byzantine fault-tolerant consensus protocols. Many such consensus protocols have a primary-backup design in which an assigned replica, the primary, is…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-07 Suyash Gupta , Jelle Hellings , Mohammad Sadoghi

In this letter, we study an unified resilient asymmetric bipartite consensus (URABC) problem for nonlinear multi-agent systems with both cooperative and antagonistic interactions under denial-of-service (DoS) attacks. We first prove that…

Systems and Control · Electrical Eng. & Systems 2023-10-02 Yi Zhang , Yichao Wang , Junbo Zhao , Shan Zuo

This article investigates a bi-objective redundancy allocation problem (RAP) for repairable systems, defined as cost minimization and availability maximization. Binary decisions jointly select the number of components and the standby…

Neural and Evolutionary Computing · Computer Science 2025-12-23 Mateusz Oszczypała , David Ibehej , Jakub Kudela

We study a model of consensus decision making, in which a finite group of Bayesian agents has to choose between one of two courses of action. Each member of the group has a private and independent signal at his or her disposal, giving some…

Statistics Theory · Mathematics 2018-04-24 Elchanan Mossel , Omer Tamuz
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