Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Collective Remote Attestation (CRA) is a well-established approach where a single Verifier attests the integrity of multiple devices in a single execution of the challenge-response protocol. Current CRA solutions are well-suited for Internet of Things (IoT ...
This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...
Decentralized signal control of congested traffic networks based on the Max-Pressure (MP) controller is theoretically proven to maximize throughput, stabilize the system and balance queues for single intersections under specific conditions. However, its pe ...
Traffic responsive signal control systems bear high potential in reducing delays in congested networks due to their ability of dynamically adjusting right-of-way assignment among conflicting movements, based on real-time traffic measurements. In this work, ...
This work examines the problem of learning the topology of a network (graph learning) from the signals produced at a subset of the network nodes (partial observability). This challenging problem was recently tackled assuming that the topology is drawn acco ...
This work investigates the benefits of a two-layer adaptive signal control framework combining multi-region perimeter control (PC) with distributed Max Pressure (MP) control in selected network intersections. Motivated by MP’s questionable performance in o ...
2022
,
The convergence speed of machine learning models trained with Federated Learning is significantly affected by non-independent and identically distributed (non-IID) data partitions, even more so in a fully decentralized setting without a central server. In ...
2022
Machine learning is currently shifting from a centralized paradigm to decentralized ones where machine learning models are trained collaboratively. In fully decentralized learning algorithms, data remains where it was produced, models are trained locally a ...
IEEE2022
,
We study the cooperative data exchange problem for fully connected networks. In this problem, nodes make broadcast transmissions to recover a file consisting of K independent packets. Each node initially only possesses a subset of the packets. We propose ( ...
2021
Time-sensitive networks, as in the context of IEEE Time-Sensitive Networking (TSN) and IETF Deterministic Networking (DetNet), offer deterministic services with guaranteed bounded latency in order to support safety-critical applications. In this thesis, we ...
