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Federated learning is a distributed machine learning paradigm through centralized model aggregation. However, standard federated learning relies on a centralized server, making it vulnerable to server failures. While existing solutions…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-03 Hongliang Zhang , Fenghua Xu , Zhongyuan Yu , Shanchen Pang , Chunqiang Hu , Jiguo Yu

Safety and assurance standards often rely on the principle that requirements errors can be minimised by expressing the requirements more formally. Although numerous case studies have shown that the act of formalising previously informal…

Software Engineering · Computer Science 2014-04-29 Ibrahim Habli , Andrew Rae

Blockchain or Distributed Ledger Technology is a disruptive technology that provides the infrastructure for developing decentralized applications enabling the implementation of novel business models even in traditionally centralized…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-22 Claudia Pop , Tudor Cioara , Ionut Anghel , Marcel Antal , Ioan Salomie

Federated Learning (FL) has emerged as a promising paradigm for collaborative model training across distributed edge devices while preserving data privacy especially with the huge increase amount of data due to the adoption of technologies…

Machine Learning · Computer Science 2026-05-18 Chaimaa Medjadji , Guilain Leduc , Sylvain Kubler , Yves Le Traon

Decentralized finance (DeFi) has become one of the most successful applications of blockchain and smart contracts. The DeFi ecosystem enables a wide range of crypto-financial activities, while the underlying smart contracts often contain…

Cryptography and Security · Computer Science 2021-04-20 Palina Tolmach , Yi Li , Shang-Wei Lin , Yang Liu

There is a lack of formalism for some key foundational concepts in systems engineering. One of the most recently acknowledged deficits is the inadequacy of systems engineering practices for engineering intelligent systems. In our previous…

Artificial Intelligence · Computer Science 2024-09-21 Niloofar Shadab , Tyler Cody , Alejandro Salado , Peter Beling

In recent years, diffusion based methods have emerged as a powerful paradigm for generative modeling. Although discrete diffusion for natural language processing has been explored to a lesser extent, it shows promise for tasks requiring…

Machine Learning · Computer Science 2025-03-25 Andrew Kiruluta , Andreas Lemos

The technology of formal software verification has made spectacular advances, but how much does it actually benefit the development of practical software? Considerable disagreement remains about the practicality of building systems with…

Software Engineering · Computer Science 2026-01-21 Li Huang , Sophie Ebersold , Alexander Kogtenkov , Bertrand Meyer , Yinling Liu

Frontier models are currently developed and distributed primarily through two channels: centralized proprietary APIs or open-sourcing of pre-trained weights. We identify a third paradigm - Protocol Learning - where models are trained across…

Machine Learning · Computer Science 2024-12-12 Alexander Long

Designing systems is typically uncertain and ambiguous at early stages. Set-based design supports alternative exploration and gradual uncertainty reduction during the early lifecycle, making it practical for complex systems design. In…

Systems and Control · Electrical Eng. & Systems 2026-05-19 Minghui Sun , Zhaoyang Chen , Georgios Bakirtzis , Hassan Jafarzadeh , Cody Fleming

The evolution of automotive technologies towards more integrated and sophisticated systems requires a shift from traditional distributed architectures to centralized vehicle architectures. This work presents a novel framework that addresses…

Software Engineering · Computer Science 2025-03-10 Sven Kirchner , Nils Purschke , Chengdong Wu , Muhammed Aqib Khan , Divye Dixit , Alois C. Knoll

In this paper, we develop new methods for the analysis of decentralized control systems and we apply them to formation control problems. The basic set-up consists of a system with multiple agents corresponding to the nodes of a graph whose…

Optimization and Control · Mathematics 2011-01-20 M. -A. Belabbas

The previous works on formalizing enterprise application integration (EAI) scenarios showed an emerging need for setting up formal foundations for integration patterns, the EAI building blocks, in order to facilitate the model-driven…

Artificial Intelligence · Computer Science 2021-04-09 Marco Montali , Andrey Rivkin , Daniel Ritter

Given an ensemble of autonomous agents and a task to achieve cooperatively, how much do the agents need to know about the state of the ensemble and about the task in order to achieve it? We introduce new methods to understand these aspects…

Optimization and Control · Mathematics 2011-01-20 M. -A. Belabbas

The advent of Federated Learning (FL) has ignited a new paradigm for parallel and confidential decentralized Machine Learning (ML) with the potential of utilizing the computational power of a vast number of IoT, mobile and edge devices…

Machine Learning · Computer Science 2022-12-06 Leon Witt , Mathis Heyer , Kentaroh Toyoda , Wojciech Samek , Dan Li

Deployment of distributed systems sets high requirements for procedures and tools for the complex testing of these systems. This work introduces a formal four-layered model for test generation mission on the basis of the component-based…

Software Engineering · Computer Science 2014-10-08 Andrey A. Shchurov , Radek Marik

We argue that recent developments in proof-of-work consensus mechanisms can be used in accordance with advancements in formal verification techniques to build a distributed payment protocol that addresses important economic drawbacks from…

Cryptography and Security · Computer Science 2020-05-14 Assimakis Kattis , Fabian Trottner

Formalization of mathematics is the process of digitizing mathematical knowledge, which allows for formal proof verification as well as efficient semantic searches. Given the large and ever-increasing gap between the set of formalized and…

Multiagent Systems · Computer Science 2021-11-23 Jin Xing Lim , Barnabé Monnot , Shaowei Lin , Georgios Piliouras

Fuzzing has become a widely adopted technique for vulnerability discovery, yet it remains ineffective for structured-input programs due to strict syntactic constraints and limited semantic awareness. Traditional greybox fuzzers rely on…

Cryptography and Security · Computer Science 2026-04-21 Yihao Zou , Tianming Zheng , Futai Zou , Yue Wu

Centralized identity management systems continuously experience security and privacy challenges, motivating the exploration of Decentralized Identity (DI) and Self-Sovereign Identity (SSI) as alternatives. Despite privacy and security…

Software Engineering · Computer Science 2026-03-26 Daria Schumm , Burkhard Stiller