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Consistent Tomography Under Partial Observations Over Adaptive Networks

Publications associées (70)

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Social Learning Under Inferential Attacks

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

A common assumption in the social learning literature is that agents exchange information in an unselfish manner. In this work, we consider the scenario where a subset of agents aims at driving the network beliefs to the wrong hypothesis. The adversaries a ...

IEEE2021

Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?

Rachid Guerraoui, Nirupam Gupta, John Stephan, Sébastien Louis Alexandre Rouault, Rafaël Benjamin Pinot

This paper addresses the problem of combining Byzantine resilience with privacy in machine learning (ML). Specifically, we study if a distributed implementation of the renowned Stochastic Gradient Descent (SGD) learning algorithm is feasible with both diff ...

ASSOC COMPUTING MACHINERY2021

Consensus Control for Decentralized Deep Learning

Martin Jaggi, Sebastian Urban Stich, Anastasiia Koloskova, Tao Lin, Lingjing Kong

Decentralized training of deep learning models enables on-device learning over networks, as well as efficient scaling to large compute clusters. Experiments in earlier works reveal that, even in a data-center setup, decentralized training often suffers fro ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Flocking-enhanced social contagion

Ignacio Pagonabarraga Mora

Populations of mobile agents-animal groups, robot swarms, or crowds of people-self-organize into a large diversity of states as a result of information exchanges with their surroundings. While in many situations of interest the motion of the agents is driv ...

AMER PHYSICAL SOC2020

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This work presents and studies a distributed algorithm for solving optimization problems over networks where agents have individual costs to minimize subject to subspace constraints that require the minimizers across the network to lie in a low-dimensional ...

IEEE2019

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

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

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

Model-based reinforcement learning and navigation in animals and machines

Dane Sterling Corneil

For decades, neuroscientists and psychologists have observed that animal performance on spatial navigation tasks suggests an internal learned map of the environment. More recently, map-based (or model-based) reinforcement learning has become a highly activ ...

EPFL2018

Decisions under Binary Messaging over Adaptive Networks

Ali H. Sayed

We consider an adaptive network made of interconnected agents engaged in a binary decision task. It is assumed that the agents cannot deliver full-precision messages to their neighbors, but only binary messages. For this scenario, a modified version of the ...

IEEE COMPUTER SOC2018