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Consistent Tomography over Diffusion Networks under the Low-Observability Regime

Related publications (32)

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Divergent X-ray tomography reconstruction and optimisation

Youssef Haouchat

In diverse fields such as medical imaging, astrophysics, geophysics, or material study, a common challenge exists: reconstructing the internal volume of an object using only physical measurements taken from its exterior or surface. This scientific approach ...

2023

Multi-agent Learning with Privacy Guarantees

Elsa Rizk

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

EPFL2023

Meta Navigation Functions: Adaptive Associations for Coordination of Multi-Agent Systems

Matin Macktoobian

In this paper, we introduce a new class of potential fields, i.e., meta navigation functions (MNFs) to coordinate multi-agent systems. Thanks to the MNF formulation, agents can contribute to each other's coordination via partial and/or total associations, ...

IEEE2022

Byzantine-Resilient Multi-Agent System

Rachid Guerraoui, Alexandre David Olivier Maurer

We consider the problem of making a multi-agent system (MAS) resilient to Byzantine failures through replication. We consider a very general model of MAS, where randomness can be involved in the behavior of each agent. We propose the first universal scheme ...

IEEE COMPUTER SOC2022

Social Learning With Partial Information Sharing

Ali H. Sayed, Virginia Bordignon

This work studies the learning abilities of agents sharing partial beliefs over social networks. The agents observe data that could have risen from one of several hypotheses and interact locally to decide whether the observations they are receiving have ri ...

IEEE2020

Consistent Tomography Under Partial Observations Over Adaptive Networks

Ali H. Sayed

This paper studies the problem of inferring whether an agent is directly influenced by another agent over a network. Agent i influences agent j if they are connected (according to the network topology), and if agent j uses the data from agent i to update i ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Tomography Of Adaptive Multi-Agent Networks Under Limited Observation

Ali H. Sayed

This work studies the problem of inferring from streaming data whether an agent is directly influenced by another agent over an adaptive network of interacting agents. Agent i influences agent j if they are connected, and if agent j uses the information fr ...

IEEE2018

Efficient Variance-Reduced Learning Over Multi-Agent Networks

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work develops a fully decentralized variance-reduced learning algorithm for multi-agent networks where nodes store and process the data locally and are only allowed to communicate with their immediate neighbors. In the proposed algorithm, there is no ...

IEEE COMPUTER SOC2018

Coordinated Optimization and Control for Smart Grids

Altug Bitlislioglu

In this thesis, we consider commercial buildings with available heating, ventilation and air conditioning (HVAC) systems, and develop methods to assess and exploit their energy storage and production potential to collectively offer ancillary services to th ...

EPFL2018

Trusted Registration, Negotiation, and Service Evaluation in Multi-Agent Systems throughout the Blockchain Technology

Michael Ignaz Schumacher, Alevtina Dubovitskaya

Some recent trends in distributed intelligent systems rely extensively on agent-based approaches. The so-called Multi Agent Systems (MAS) are taking over the management of sensitive data on behalf of their producers and users (e.g., medical records, financ ...

IEEE2018