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Related papers: Weaker Assumptions for Asymmetric Trust

200 papers

In a previous FAST paper, I presented a quantitative model of the process of trust building, and showed that trust is accumulated like wealth: the rich get richer. This explained the pervasive phenomenon of adverse selection of trust…

Cryptography and Security · Computer Science 2015-05-20 Dusko Pavlovic

In this paper, a generalization of the traditional point-to-point to communication setup, which is named as "reliable communications with asymmetric codebooks", is proposed. Under the assumption of independent identically distributed…

Information Theory · Computer Science 2008-09-12 Yucel Altug , M. Kivanc Mihcak , Onur Ozyesil , Vishal Monga

We study the problem of communication over a compound quantum channel in the presence of entanglement. Classically such channels are modeled as a collection of conditional probability distributions wherein neither the sender nor the…

Quantum Physics · Physics 2019-03-19 Anurag Anshu , Rahul Jain , Naqueeb Ahmad Warsi

In the near future, there will likely be special-purpose quantum computers with 40-50 high-quality qubits. This paper lays general theoretical foundations for how to use such devices to demonstrate "quantum supremacy": that is, a clear…

Quantum Physics · Physics 2016-12-28 Scott Aaronson , Lijie Chen

Voting algorithms have been widely used as consensus protocols in the realization of fault-tolerant systems. These algorithms are best suited for distributed systems of nodes with low computational power or heterogeneous networks, where…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-16 Sebastian Müller , Andreas Penzkofer , Darcy Camargo , Olivia Saa

What are the key-features that enable an information diffusion model to explain the inherent dynamic, and often competitive, nature of real-world propagation phenomena? In this paper we aim to answer this question by proposing a novel class…

Social and Information Networks · Computer Science 2018-05-30 Antonio Caliò , Andrea Tagarelli

We present Cobalt, a novel atomic broadcast algorithm that works in networks with non-uniform trust and no global agreement on participants, and is probabilistically guaranteed to make forward progress even in the presence of maximal faults…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-21 Ethan MacBrough

We study distribution-free predictive inference for data with group symmetries, aiming to establish near-conditional coverage guarantees beyond exchangeability for structured data. While many predictive inference methods achieve a target…

Methodology · Statistics 2026-05-19 Yichen Shen , Mengxin Yu

Systems such as sensor networks and teams of autonomous robots consist of multiple autonomous entities that interact with each other in a distributed, asynchronous manner. These entities need to keep track of the state of the system as it…

Artificial Intelligence · Computer Science 2012-07-09 Avi Pfeffer , Terry Tai

Most modern asset transfer systems use consensus to maintain a totally ordered chain of transactions. It was recently shown that consensus is not always necessary for implementing asset transfer. More efficient, asynchronous solutions can…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-09 Petr Kuznetsov , Yvonne-Anne Pignolet , Pavel Ponomarev , Andrei Tonkikh

This paper proposes a novel approach to resilient distributed optimization with quadratic costs in a networked control system (e.g., wireless sensor network, power grid, robotic team) prone to external attacks (e.g., hacking, power outage)…

Systems and Control · Electrical Eng. & Systems 2025-02-11 Luca Ballotta , Giacomo Como , Jeff S. Shamma , Luca Schenato

Given that distributed systems face adversarial behaviors such as eavesdropping and cyberattacks, how to ensure the evidence fusion result is credible becomes a must-be-addressed topic. Different from traditional research that assumes nodes…

Cryptography and Security · Computer Science 2024-12-10 Chaoxiong Ma , Yan Liang

We study distributed computation in synchronous dynamic networks where an omniscient adversary controls the unidirectional communication links. Its behavior is modeled as a sequence of directed graphs representing the active (i.e. timely)…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-20 Martin Biely , Peter Robinson , Ulrich Schmid

Errors quoted on results are often given in asymmetric form. An account is given of the two ways these can arise in an analysis, and the combination of asymmetric errors is discussed. It is shown that the usual method has no basis and is…

Data Analysis, Statistics and Probability · Physics 2014-11-18 Roger Barlow

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

This paper investigates an expected average error for distributed averaging problems under asynchronous updates. The asynchronism in this context implies no existence of a global clock as well as random characteristics in communication…

Systems and Control · Electrical Eng. & Systems 2020-06-04 Kooktae Lee

Crowdsourced data supports real-time decision-making but faces challenges like misinformation, errors, and contributor power concentration. This study systematically examines trust management practices across platforms categorised as…

Social and Information Networks · Computer Science 2025-11-06 Iffat Gheyas , Muhammad Rizwan Asghar , Steve Schneider , Alan Woodward

This paper studies asymptotic consensus in systems in which agents do not necessarily have self-confidence, i.e., may disregard their own value during execution of the update rule. We show that the prevalent hypothesis of self-confidence in…

Dynamical Systems · Mathematics 2015-03-27 Thomas Nowak

Conformal prediction is a popular, modern technique for providing valid predictive inference for arbitrary machine learning models. Its validity relies on the assumptions of exchangeability of the data, and symmetry of the given model…

Methodology · Statistics 2023-03-20 Rina Foygel Barber , Emmanuel J. Candes , Aaditya Ramdas , Ryan J. Tibshirani

This thesis scrutinizes common assumptions underlying traditional machine learning approaches to fairness in consequential decision making. After challenging the validity of these assumptions in real-world applications, we propose ways to…

Machine Learning · Computer Science 2021-02-01 Niki Kilbertus