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Efficient Variance-Reduced Learning Over Multi-Agent Networks

Publications associées (48)

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Consistent Tomography over Diffusion Networks under the Low-Observability Regime

Ali H. Sayed, Augusto José Rabelo Almeida Santos

This work considers a diffusion network responding to streaming data, and studies the problem of identifying the topology of a subnetwork of observable agents by tracking their output measurements. Topology inference from indirect and/or incomplete dataset ...

IEEE2018

Decentralized exact coupled optimization

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This work develops an exact converging algorithm for the solution of a distributed optimization problem with partially-coupled parameters across agents in a multi-agent scenario. In this formulation, while the network performance is dependent on a collecti ...

2017

Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Hadrien Hendrikx

In reinforcement learning, agents learn by performing actions and observing their outcomes. Sometimes, it is desirable for a human operator to \textit{interrupt} an agent in order to prevent dangerous situations from happening. Yet, as part of their learni ...

EPFL2017

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We present novel, low-cost and non-invasive potential diagnostic biomarkers of schizophrenia. They are based on the 'mirrorgame', a coordination task in which two partners are asked to mimic each other's hand movements. In particular, we use the patient's ...

2017

Exact Diffusion for Distributed Optimization and Learning---Part I: Algorithm Development

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work develops a distributed optimization strategy with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown in Part II to have a wider stability range and superior conv ...

2017

Comparative assessment of selected sugarcane biorefinery-centered systems in Brazil: A multi-criteria method based on sustainability indicators

Edgard Gnansounou, Elia Mercedes Ruiz Pachon, Pavel Vaskan, Catarina Marciano Alves

This work proposes a new sustainability assessment framework aiming to compare selected options of biorefineries subject to provide the same services to a community. At this end, a concept of biorefinery-centered system helps to develop a joint resources a ...

Elsevier2017

Dynamic resource assignment is a common problem in multi-agent systems. We consider scenarios in which dynamic agents have preferences about assignments and the resources that can be assigned using online auctions. We study the trade-off between the follow ...

Ios Press2016

Part I of this paper examined the mean-square stability and convergence of the learning process of distributed strategies over graphs. The results identified conditions on the network topology, utilities, and data in order to ensure stability; the results ...

IEEE2015

Adaptation, Learning, and Optimization over Networks

Ali H. Sayed

This work deals with the topic of information processing over graphs. The presentation is largely self-contained and covers results that relate to the analysis and design of multi-agent networks for the distributed solution of optimization, adaptation, and ...

NOW Publishers2014

We consider the problem of dictionary learning over large scale models, where the model parameters are distributed over a multi-agent network. We demonstrate that the dual optimization problem for inference is better conditioned than the primal problem and ...

IEEE2014