相关论文: Committee selection in DAG distributed ledgers and…

In speaker diarization, traditional clustering-based methods remain widely used in real-world applications. However, these methods struggle with the complex distribution of speaker embeddings and overlapping speech segments. To address…

Federated learning allows a group of distributed clients to train a common machine learning model on private data. The exchange of model updates is managed either by a central entity or in a decentralized way, e.g. by a blockchain. However,…

A companion paper defined the notion of digital social contracts, presented a design for a social-contracts programming language, and demonstrated its potential utility via example social contracts. The envisioned setup consists of people…

Recently, a new generation of P2P systems capable of addressing data integrity and authenticity has emerged for the development of new applications for a "more" decentralized Internet, i.e., Distributed Ledger Technologies (DLT) and…

Bayesian networks, with structure given by a directed acyclic graph (DAG), are a popular class of graphical models. However, learning Bayesian networks from discrete or categorical data is particularly challenging, due to the large…

This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into…

Structural learning of directed acyclic graphs (DAGs) or Bayesian networks has been studied extensively under the assumption that data are independent. We propose a new Gaussian DAG model for dependent data which assumes the observations…

Judgment aggregation problems form a class of collective decision-making problems represented in an abstract way, subsuming some well known problems such as voting. A collective decision can be reached in many ways, but a direct one-step…

This paper considers the distributed consensus problem of multi-agent systems with general continuous-time linear dynamics. Two distributed adaptive dynamic consensus protocols are proposed, based on the relative output information of…

Distributed ledger systems, such as blockchains, rely on consensus protocols that commit ordered messages for processing. In practice, message ordering within these systems is often reward-driven. This raises concerns about fairness,…

Nakamoto Consensus achieves a decentralized ledger through a single-chain blockchain, assuming a maximum network delay, which limits block generation speed, resulting in low throughput. \cite{pg2018} (PG) enhances throughput using a…

We provide the first large-scale data collection of real-world approval-based committee elections. These elections have been conducted on the Polkadot blockchain as part of their Nominated Proof-of-Stake mechanism and contain around one…

Most online lotteries today fail to ensure the verifiability of the random process and rely on a trusted third party. This issue has received little attention since the emergence of distributed protocols like Bitcoin that demonstrated the…

Recently continuous relaxations have been proposed in order to learn Directed Acyclic Graphs (DAGs) from data by backpropagation, instead of using combinatorial optimization. However, a number of techniques for fully discrete…

Privacy-preserving data analysis has become more prevalent in recent years. In this study, we propose a distributed group differentially private Majority Vote mechanism, for the sign selection problem in a distributed setup. To achieve…

With the introduction of the term blockchain in 2008, its interest has been increasing in the community since the idea was coined. The reason for this interest is because it provides anonymity, security and integrity without any central…

This paper presents continuous dynamic average consensus (DAC) algorithms for a group of agents to estimate the average of their time-varying reference signals cooperatively. We propose consensus algorithms that are robust to agents joining…

This paper presents a distributed resource selection mechanism for diverse cloud-edge environments, enabling dynamic and context-aware allocation of resources to meet the demands of complex distributed applications. By distributing the…

Learning directed acyclic graphs (DAGs) from data is a challenging task both in theory and in practice, because the number of possible DAGs scales superexponentially with the number of nodes. In this paper, we study the problem of learning…

This paper studies the behavior of a strategic aggregator offering regulation capacity on behalf of a group of distributed energy resources (DERs, e.g. plug-in electric vehicles) in a power market. Our objective is to maximize the…