Dyck paths with catastrophes modulo the positions of a given pattern
Jean-Luc Baril, Sergey Kirgizov, Armen Petrossian
pdf arXiv Submitted.

Enumeration of Dyck paths with air pockets
Jean-Luc Baril, Sergey Kirgizov, Rémi Maréchal, and Vincent Vajnovszki
pdf arXiv Submitted.

Q-bonacci words and numbers
Sergey Kirgizov
pdf arXiv Submitted.

Asymptotic bit frequency in Fibonacci words
Jean-Luc Baril, Sergey Kirgizov, and Vincent Vajnovszki
pdf arXiv To be presented at GASCom2022

Gray codes for Fibonacci q-decreasing words
Jean-Luc Baril, Sergey Kirgizov and Vincent Vajnovszki
pdf arXiv Submitted.

Lattice paths with a first return decomposition constrained by the maximal height of a pattern
pdf arXiv
Jean-Luc Baril and Sergey Kirgizov
Discrete Mathematics Letters, Volume 8, 2022.

Pattern statistics in faro words and permutations pdf arXiv
Jean-Luc Baril, Alexander Burstein and Sergey Kirgizov
Discrete Mathematics, Volume 344, Issue 8, August 2021

Bijections from Dyck and Motzkin meanders with catastrophes to pattern avoiding Dyck paths pdf arXiv
Discrete Mathematics Letters, Volume 7, 2021
Jean-Luc Baril and Sergey Kirgizov

Transformation à la Foata for special kinds of descents and excedances pdf arXiv
Enumerative Combinatorics and Applications, ECA 1:3 (2021) Article S2R19
Jean-Luc Baril and Sergey Kirgizov

Vive les équations des motifs et les équations des statistiques !
Pattern distributions in Dyck paths with a first return decomposition constrained by height pdf arXiv
Discrete Mathematics, Volume 343, Issue 9, September 2020
Jean-Luc Baril, Richard Genestier and Sergey Kirgizov

Bijections between directed animals, multisets and Grand-Dyck paths pdf arXiv
The Electronic Journal of Combinatorics Volume 27, Issue 2 (2020), Article P2.10
Jean-Luc Baril, David Bevan and Sergey Kirgizov

Motzkin paths with a restricted first return decomposition pdf
INTEGERS 19, September 2019
Jean-Luc Baril, Sergey Kirgizov and Armen Petrossian

Enumeration of Łukasiewicz paths modulo some patterns pdf
Discrete Mathematics, Volume 342, Issue 4, April 2019
Jean-Luc Baril, Sergey Kirgizov and Armen Petrossian

Descent distribution on Catalan words avoiding a pattern of length at most three pdf arXiv
Discrete Mathematics, Volume 341, Issue 9, September 2018
Jean-Luc Baril, Sergey Kirgizov and Vincent Vajnovszki

Dyck paths with a first return decomposition constrained by height pdf
Discrete Mathematics, Volume 341, Issue 6, June 2018
Jean-Luc Baril, Sergey Kirgizov and Armen Petrossian

Forests and pattern avoiding permutations modulo pure descents pdf
Pure Mathematics and Applications, Volume 27, Issue 1, 06 August 2018 Jean-Luc Baril, Sergey Kirgizov and Armen Petrossian

Patterns in treeshelves pdf arXiv:1611.07793
Discrete Mathematics, Volume 340, Issue 12, 2017
Jean-Luc Baril, Sergey Kirgizov and Vincent Vajnovszki

The pure descent statistic on permutations pdf
Discrete Mathematics, Volume 340, Issue 10, October 2017
Jean-Luc Baril, Sergey Kirgizov

Information fusion-based approach for studying influence on twitter using belief theory pdf
Computational Social Networks, Volume 3, Issue 1, 2016
Lobna Azaza, Sergey Kirgizov, Marinette Savonnet, Éric Leclercq, Nicolas Gastineau, and Rim Faiz

The complexity of deciding whether a graph admits an orientation with fixed weak diameter .hal
Discrete Mathematics & Theoretical Computer Science (DMTCS), Volume 17, Issue 3, 2016
Julien Bensmail, Romaric Duvignau, Sergey Kirgizov

Suppression distance computation for hierarchical clusterings .hal
Information Processing Letters, Volume 115, Issue 9, 2015
François Queyroi and Sergey Kirgizov

Towards realistic modeling of IP-level routing topology dynamics pdf
Networking Science, Volume 3, Issue 1-4, December 2013
Clémence Magnien, Amélie Medem, Sergey Kirgizov and Fabien Tarissan

Clique percolation method: memory efficient almost exact communities pdf arXiv
Alexis Baudin, Maximilien Danisch, Sergey Kirgizov, Clémence Magnien and Marwan Ghanem
17th anniversary of the International Conference on Advanced Data Mining and Applications, (ADMA’21) , Sydney, Australia, 2-4 February, 2022

Qubonacci words
Permutations patterns 2021, June 15-16
Joint work with Jean-Luc Baril and Vincent Vajnovszki
Look at my slides, and one page abstract of our work.

Pattern distribution in faro words and permutations
Permutations patterns 2020, June 30 and July 1
Joint work with Jean-Luc Baril
Look at a .pdf poster, a short video (5 min) and a two page abstract our our work.

Temporal density of community structure
MARAMI 2019, Dijon, 8 Novembre 2019. Slides
together with Éric Leclercq

Pattern avoiding permutations modulo pure descent
Permutation Patterns Conference at Reykjavik University, Iceland, 2017
Jean-Luc Baril, Sergey Kirgizov and Armen Petrossian

Temporal density of complex networks and ego-community dynamics pdf
Annual Conference on Complex Systems (ECCS or CCS), Amsterdam, 19-22 September, 2016 Éric Leclercq, Sergey Kirgizov

Towards a Twitter Observatory: A multi-paradigm framework for collecting, storing and analysing tweets preprint.pdf
RCIS 2016, IEEE Tenth International Conference on Research Challenges in Information Science, Grenoble, France, 1-3 June 2016
Ian Basaille, Sergey Kirgizov, Éric Leclercq, Marinette Savonnet, et Nadine Cullot

A web application for event detection and exploratory data analysis for Twitter data pdf

Influence Assessment in Twitter Multi-Relational Network pdf
Eleventh International IEEE Conference on Signal Image Technologies and Internet-Based System (SITIS), Bangkok, Thailand, 2015
Lobna Azaza, Sergey Kirgizov, Marinette Savonnet, Éric Leclercq, Rim Faiz

On the complexity of turning a graph into the analogue of a clique pdf

(best paper award) Using Reinforcement Learning for Autonomic Resource Allocation in Clouds: towards a fully automated workflow pdf
Seventh International Conference on Autonomic and Autonomous Systems, ICAS 2011, pages 67-74, 2011
Xavier Dutreilh, Sergey Kirgizov, Olga Melekhova, Jacques Malenfant, Nicolas Rivierre and Isis Truck

SNFreezer: a Platform for Harvesting and Storing Tweets in a Big Data Context
Éric Leclercq, Marinette Savonnet, Thierry Grison, Sergey Kirgizov & Ian Basaille
chapter of the book Tweets from the Campaign Trail: Researching Candidates' Use of Twitter during the European Parliamentary Elections
ed Frame, A., Mercier, A., Brachotte, G., & Thimm, C.
Bern, Switzerland: Peter Lang D. Retrieved Sep 29, 2017

Évaluation de l’influence polarisée dans un réseau multi-relationnel : application à twitter .htm
Document Numérique, Volume 20, Issue 1, 2017
Lobna Azaza, Marinette Savonnet, Éric Leclercq, Sergey Kirgizov, and Rim Faiz

Un observatoire pour la modélisation et l’analyse des réseaux multi-relationnels. Une application à l’étude du discours politique sur Twitter .htm
Document Numérique, Volume 20, Issue 1, 2017
Ian Basaille, Eric Leclercq, Marinette Savonnet, Nadine Cullot, Sergey Kirgizov, Thierry Grison, Elisabeth Gavignet

Packing coloring and subsets preserving path distance slides.pdf and abstract.pdf
Les 18es Journées Graphes et Algorithmes, Paris, 16-18 Novembre, 2016
Nicolas Gastineau, Benjamin Gras, Sergey Kirgizov, Mahmoud Omidvar

(Re)constuire la temporalité d’un événement médiatique sur Twitter : une étude contrastive
(Re)constructing the temporality of media events on Twitter: a contrastive study
XXe Congrès de la SFSIC: Temps, temporalités et information-communication, Metz, France, 8-10 June 2016 Tatiana Kondrashova, Alexander Frame, Sergey Kirgizov

Évaluation de l’influence dans un réseau multi-relationnel : le cas de Twitter
INFORSID’2016, Le congrès INFORSID (INFormatique des ORganisations et Systèmes d’Information et de Décision), du 31 mai au 3 juin, à Grenoble, France, 2016
Lobna Azaza, Sergey Kirgizov, Marinette Savonnet, Éric Leclercq, Rim Faiz

A la recherche des mini-publics : un problème de communautés, de singularités et de sémantique pdf
16ème conférence francophone sur l’Extraction et la Gestion des Connaissances (EGC 2016): l’atelier Données participatives et sociales), Reims, France, Janvier 2016
Éric Leclercq, Sergey Kirgizov and Maximilien Danisch

Evaluation de l’influence sur Twitter: Application au projet “Twitter aux Elections Européennes 2014” pdf
Journée d’étude Etudier le Web politique : Regards croisés, Lyon, 2015
Lobna Azaza, Sergey Kirgizov, Éric Leclercq, Marinette Savonnet, Alexander Frame

Papersᵞ, Discussing board for scientific papers (pdf)
Conference SO Data 3, Paris, France, 26 Mars 2015
Sergey Kirgizov

Internet Topology Dynamics: stochastic process estimation from partial observations Journée jointe des GDR ISIS et Phénix “Analyse et inférence pour les réseaux”), Paris, 2013
Sergey Kirgizov and Clémence Magnien

Distribution multimodale de la taille du sous-graphe des plus courts chemins dans un graphe aléatoire pdf
Journées Graphes et Algorithmes (JGA), Orsay, Novembre 2013
Sergey Kirgizov

Dynamique de la topologie de l’internet : impact de la fréquence de mesure sur les observations slides
Studying the impact of measurement frequency on the IP-level routing topology dynamics paper
24ème colloque Gretsi, Brest, France, 2013
Sergey Kirgizov, Clémence Magnien, Fabien Tarissan and Azhu Liu

Vers une modélisation réaliste de la dynamique de la topologie de routage au niveau IP pdf
Journées Automnales 2012 ResCom, Paris, 2012
Sergey Kirgizov, Amélie Medem, Clémence Magnien, Fabien Tarissan

The limit of generalised Dempster-Shafer-Smets operator draft.pdf, 2016
Sergey Kirgizov, Nicolas Gastineau, Lobna Azaza

A new graph density (SJS article), 2015
For a given graph G we propose the non-classical definition of its true density: ρ(G) = Mass(G)/Vol (G), where the Mass of the graph G is a total mass of its links and nodes, and Vol (G) is a size-like graph characteristic, defined as a function from all graphs to R ∪ ∞. We show how the graph density ρ can be applied to evaluate communities, i.e “dense” clusters of nodes.

Peaks and valleys in the size distribution of shortest path subgraphs pdf , 2014
Sergey Kirgizov and Clémence Magnien, preprint

Metric space of hierarchies, 2013 pdf
We explain how to turn a set of all hierarchical clusterings of a graph into a metric space, using classical Hausdorff and Levenshtein distances.

Stochastic process estimation from partial observations: Poisson case pdf, 2014
Sergey Kirgizov, François Queyroi
Having a sequence of values v_0, v_{1∆} , v_{2∆} , . . . , v_{N∆}, which are measured every ∆ units of time, usually we are interested in the prediction of the future outcome of this sequence at time (N + 1)∆. But in some real-world cases we want to know, not the future, but rather the truth about the present: if Maria performs more observations per unit of time than Maximilian, how can he estimates the Maria’s results from his own? In this small note we consider the situation when the underlying process is Poissonian.