NATALE , Emanuele

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We consider theRelative-Majority Problem(also known asPlurality), in which, given amulti-agent system where each agent is initially provided an input value out of a set ofkpossible ones,each agent is required to eventually compute the input valuewith the highest frequency in the initialconfiguration. We consider the problem in the general...

Error-correcting codes are efficient methods for handling noisy communication channels in the context of technological networks. However, such elaborate methods differ a lot from the unsophisticated way biological entities are supposed to communicate. Yet, it has been recently shown by Feinerman, Haeupler, and Korman [PODC 2014] that complex...

The International Symposium on Experimental Algorithms (SEA) is an international forum for researchers in the area of the design, analysis, and experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications (telecommunications, transport, bioinformatics, cryptography,...

We present KADABRA, a new algorithm to approximate betweenness centrality in directed and undirected graphs, which significantly outperforms all previous approaches on real-world complex networks. The efficiency of the new algorithm relies on two new theoretical contributions, of independent interest. The first contribution focuses on sampling...

Integrated assessment models are critical tools for scientists to understand the complex interactions between human and natural systems, and for policymakers to design effective policies to tackle global societal and environmental challenges. However, the lack of transparency and reproducibility of the models hinders their use and trust in...

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International audience

We study parallel \emph{Load Balancing} protocols for a client-server distributed model defined as follows. There is a set $\sC$ of $n$ clients and a set $\sS$ of $n$ servers where each client has (at most) a constant number $d \geq 1$ of requests that must be assigned to some server. The client set and the server one are connected to each...

International audience

We investigate the behavior of a simple majority dynamics on networksof agents whose interaction topology exhibits a community structure. Byleveraging recent advancements in the analysis of dynamics, we prove that,when the states of the nodes are randomly initialized, the system rapidlyand stably converges to a configuration in which the...

There has recently been an increasing desire to evaluate neural networks locally on computationally-limited devices in order to exploit their recent effectiveness for several applications; such effectiveness has nevertheless come together with a considerable increase in the size of modern neural networks, which constitute a major downside in...

In several real Multi-Agent Systems (MAS), it has been observed that only weaker forms of metastable consensus are achieved, in which a large majority of agents agree on some opinion while other opinions continue to be supported by a (small) minority of agents. In this work, we take a step towards the investigation of metastable consensus...

Distributed Computing Column 77

Journal version of https://hal.science/hal-02487650v2.

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In the deterministic binary majority process we are given a simple graph where each node has one out of two initial opinions. In every round, each node adopts the majority opinion among its neighbors. It is known that this process always converges in O(|E|) rounds to a two-periodic state in which every node either keeps its opinion or changes...

The dataset contains a collection of temporal brain networks. The networks are obtained from resting-state fMRI data of 1047 subjects from the Human Connectome Project (HCP).

We investigate the problem of making a neural network perform some hidden computation whose result can be easily retrieved from the network output. In particular, we consider the following scenario. A user is provided a neural network for a classification task by a company. We further assume that the company has limited access to the user's...

We investigate the problem of making an artificial neural network perform hidden computations whose result can be easily retrieved from the network's output. In particular, we consider the following scenario. A user is provided a neural network for a classification task by a third party. The user's input to the network contains sensitive...

The lottery ticket hypothesis states that a randomly-initialized neural network contains a small subnetwork which, when trained in isolation, can compete with the performance of the original network. Recent theoretical works proved an even stronger version: every sufficiently overparameterized (dense) neural network contains a subnetwork that,...

Null models are crucial for determining the degree of significance when testing hypotheses about brain dynamics modeled as a temporal complex network [7, 12]. The comparison between the hypothesis being tested on empirical data and on the null model enables us to assess the extent to which an apparently remarkable feature of the former can be...

Brain dynamics can be modeled as a temporal brain network starting from the activity of different brain regions in functional magnetic resonance imaging (fMRI) signals. When validating hypotheses about temporal networks, it is important to use an appropriate statistical null model that shares some features with the treated empirical data. The...

Abstract The 2-Choices dynamics is a process that models voting behavior on networks and works as follows: Each agent initially holds either opinion blue or red ; then, in each round, each agent looks at two random neighbors and, if the two have the same opinion, the agent adopts it. We study its behavior on a class of networks with...

International audience