News

  • EUSIPCO 2025: The paper Online centralized non-parametric change-point detection via graph-based likelihood-ratio estimation has been accepted to the European Signal Processing Conference (EUSIPCO) 2025. Co-authored with A. de la Concha and N. Vayatis.
  • PhD defense: on the 19th May, 2025, Alejandro de la Concha has successfully defended his PhD thesis on “Graph-based machine learning for detection tasks on complex systems“. Bravo Alex!! Proud for him and his excellent work.
  • JdS 2025: Three works from our team will be presented at the Journée de Statistique 2025 (french conference of the Statistics community),
    • Fusing multiple data views with diffusion maps. G. Debaussart and A. Kalogeratos.
    • Graph-based weight cascading methods for multisite time series forecasting. E. Campagne at al.
    • Identification of structure features of graphs to improve GNN performance. Itai Zehavi et al.
  • Workshop: A. de la Concha presented the joint work on Collaborative two-sample testing to the ELSA Workshop on Privacy-Preserving Machine Learning 2025, organized by the ELLIS netowork.
  • Workshop: A workshop dedicated to diffusion of opinions and disinformation will take place on the 4th of April 2025 at EHESS-Paris. Co-organization of CAMS and Centre Borelli.
  • MLMDA is dead – Long live LIPS: Our research team has be renamed to Learning and Information Processing Systems – LIPS. Read more details can be found here.
  • New interns:
    • Yutai Zhao (M2 MHPC P.S.) on stream diversification (Apr–Oct).
    • Mahdi Hadj Taieb (M1 ENSTA Paris) on modeling and learning from social network activity (Jun-Aug).
    • Itai Zehavi (M1 ENS P.S. ARIA) on large-scale electricity forecasting (Feb-Jul, in collaboration with EDF).
    • Hacini Malik (L3 ENSIMAG Grenoble) on graph representation learning (Jun-Oct).
    • Yann Moinard and Nidhal Sellik (L3 ENS P.S. Maths) on particle-based global optimization schemes (Mar-Jun).
  • Code: The code of a prototype implementation of the GSM-Degroot model is now available here].
  • AISTATS 2025:  Two papers will appear at the 28th International Conference on Artificial Intelligence and Statistics (AISTATS).
    • Collaborative non-parametric two-sample testing, co-authored with A. de la Concha and N. Vayatis [pdf].
    • Stein Boltzmann Sampling: A Variational Approach for Global Optimization, co-authored with G. Serré, and N. Vayatis [pdf].
  • New intern:
    • Itai Zehavi (M1 ENS P.S. ARIA) on a graph signal processing validation approach for forecasting methods (Oct-Jan).
  • FMJH Post-doc funding: The Foundation has announced the call for post-doc funding 2024. Check a subject proposal entitled Predictive maintenance for networked systems. Applications are due to the 9th of December [link].
  • EDF Challenge: The EDF Data Challenge (our student Eloi Campagne leads the organization team) is still open for contributions on the problem of forecasting electricity load (consumption). Feel free to diffuse and contribute!
  • SETN2024: A new paper with the title LIPO+: Frugal Global Optimization for Lipschitz Functions, co-authored with G. Serré (PhD student, CB), P. Beja-Battais (PhD student, CB), S. Chirrane, and N. Vayatis, will appear in EETN Conference on Artificial Intelligence. [pdf]
  • W@ECML2024: A new paper with the title Leveraging Graph Neural Networks to Forecast Electricity Consumption, co-authored with Eloi Campagne (PhD student, EDF&CB), Yvenn Amara-Ouali, and Yannig Goude, will appear at the European Conference on Machine Learning – Workshop ML4SPS (with proceedings), 2024. [pdf]
  • JdS 2024: Eloi Campagne (PhD student, EDF&CB) presented his work on the Forecasting Net Load in France – EDF Challenge 2024, at the 55th Journées de Statistique (JdS 2024, SFdS), in May, Bordeaux, France. Joint work with Yvenn Amara-Ouali and Yannig Goude from EDF. [pdf]
  • New interns:
    • Louise Allain (M2 MVA, Apr–Oct) on non-parametric graph inference.
    • Silviu-Adrian Predoi (M1 ENS P.S. Physics) on node embeddings (Apr-Sep).
    • Tokinirina Hansen and Yorick Libiot (L3 ENS P.S. Maths) on random walks over graphs.
  • Preprint: A new priprint with the title Collaborative non-parametric two-sample testing, co-authored with A.de la Concha, and N. Vayatis, 2024. [pdf]
  • Preprint: A new priprint with the title Stein Boltzmann Sampling: A Variational Approach for Global Optimization, co-authored with G. Serré, and N. Vayatis, 2024. [pdf]
  • AISTATS 2024: The paper Online non-parametric likelihοod-ratio estimation by Pearson-divergence functional minimization. with A. de la Concha and N. Vayatis, will appear in the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 [pdf].
  • Preprint: Significant update to the work Collaborative likelihood-ratio estimation over graphs, co-authored with A. de la Concha, and N. Vayatis, can be found at [pdf].
  • Preprint: The new preprint UniForCE: The unimodality forest method for clustering and estimation of the number of clusters, co-authored with G. Vardakas and A. Likas, can be found at [pdf][code].
  • Preprint: The new preprint Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization, co-authored with A. de la Concha and N. Vayatis, can be found at [pdf].
  • New interns:
    • Jeanne Belly (M1 ENS P.S. ARIA) on social network study of propagation phenomena.
    • Teo Tessier (M1 ENS P.S. ARIA) on graph generation methods.
  • New PhD student:
    Eloi Campagne will work on forecasting electricity consumption in a Cifre Phd with EDF. Co-supervised with Mathilde Mougeot from CB, Yvenn Amara-Ouali and Yannig Goude from EDF.
  • ΤCSS: The article DeGroot-based opinion formation under a global steering mechanism, co-authored with I. Conjeaud and P. Lorenz-Spreen, has been accepted to the journal IEEE Transactions on Computational Social Systems (TCSS, impact factor: 4.75) [pdf][code].
  • RTE-SNCF: Launch of a new ambitious project with RTE and SNCF, also in collaboration with Eurobios. Machine learning, operational research, and network science, toward modern scalable predictive maintenance.
  • CNA2023: An extended abstract under the title Opinion formation under global steering with application to social network data analysis will be presented at the Complex Networks 2023 conference [pdf][slides]. This refers to the following long full paper that is co-authored with Ivan Conjeaud and Philipp Lorenz-Spreen.
  • ICTAI2023: The paper A framework for paired-sample hypothesis testing for high-dimensional data, co-authored with I. Bargiotas and N. Vayatis, will appear in the IEEE International Conference on Tools with Artificial Intelligence 2023 [pdf].
  • New PhD students:
    • Gaëtan Serré, co-supervision with Nicolas Vayatis
    • Gwendal Debaussart
    • Gaspard Abel, co-supervision with Julien Randon-Furling and Jean-Pierre Nadal.
  • ARIA topics: Some topics are now available for the new students of the ARIA program.
  • Invited Talk: At the 10th International Workshop on Applied Probability (IWAP) 2023 at Thessaloniki, I talked about the Warm-starting selection process and  its multi-round extention.
  • New interns:
    • Perceval Beja-Battais (M2 MVA, Apr – Oct) will work on learning theory.
    • Gaëtan Serré (M2 MVA, Apr – Oct) will work on global optimization.
    • Gwendal Debaussart (M2 MVA, Apr – Oct) will work on statistical machine learning.
    • Eloi Campagne (M2 MVA, Apr – Oct) will work on time-series analysis and prediction (colab. with EDF).
    • Gaspard Abel (M2 ENS PS Physics) on information diffusion, co-supervision with Jean-Pierre Nadal.
    • Mohamed Aymen Bouyahia (M1 ENSTA Paris, May – August) will work on interpretable ML.
    • Abdeljalil Zoubir (UM6P PhD visiting as an intern from Morocco, Apr – July) on graph neural networks with application to chemical compounds.
    • Manon Gouttefangeas and David Pieroucci (L3 ENS Maths, Apr – Jun) on paired sample hypothesis testing.
    • Quentin Boiret and Amer Essakine (L3 ENS Maths, Apr – Jun) on graph neural networks for time series.
  • Preprint: The new preprint Online Centralized Non-parametric Change-point Detection via Graph-based Likelihood-ratio Estimation, co-authored with A. de la Concha and N. Vayatis, can be found at [pdf].
  • Round table: I will be part of the 4-person panel of the Alumni Event organized by the Dept. Computer Science and Engineering of University of Ioannina on 9 Dec 2022 [blog post][poster].
  • Workshop: The work Collaborative likelihood-ratio estimation over graphs [paper][slides][poster] will be presented by Alejandro de la Concha in NeurIPS@Paris 2022 [program] on 23 Nov.
  • Post-doc call: The Foundation FMJH has announced the call for post-doc fellowships. Check our subject proposal entitled Graph operator pursuit for efficient graph machine learning. Applications are due to the 1st of December. Contact me for more details.
  • Preprint: The new preprint DeGroot-based opinion formation under a global steering mechanism, co-authored with I. Conjeaud and P. Lorenz-Spreen, can be found at [pdf].
  • Preprint: The new preprint Clustering for directed graphs using parametrized random walk diffusion kernels, co-authored with H. Sevi and M. Jonckeere, can be found at [pdf].
  • Workshop: The Paris-Saclay Change-Point workshop has just be announced. It is organized by members of our team, and it’s going to be held on Monday-Tuesday 16-17 January 2023 at ENS Paris-Saclay.
  • ICANN2022: The paper To tree or not to tree? Assessing the impact of smoothing the decision boundaries, co-authored with A. Merida and M. Mougeot, will appear in the Int. Conf. on Artificial Neural Networks (ICANN 2022) [pdf].
  • FMJH funding: Great news to share: Harry Sevi will be funded for a 2-years post-doctoral fellowship by the Foundation for Mathematics Jacque Hadamard (FMJH) to work with me and the MLMDA team on the project “Using the graph structure to survive in high-dimensions: Graph arrangements, walks, and embeddings“.
  • Preprint: The new preprint Collaborative likelihood-ratio estimation over graphs, co-authored with A. de la Concha, and N. Vayatis, can be found at [pdf].
  • Conf. Talk:  Our PhD student Anthea Merida will present orally her work on “Data inspection via challenging decision boundaries’ rigidity” at the Int. Conf. of Computational Statistics – COMPSTAT 2022.
  • New interns:
    • Mohammed Hssein (M2 MVA, May-Oct) will work on Federated Learning.
    • Jules Tsukahara (M2 MVA, May-Oct) will work on graph representation learning.
    • Florian Châtel (L3 Maths, ENS Paris-Saclay, Apr – Jun) will work on interpretable ML.
    • Antonin Casel and Ilyes Belkacem (L3 Maths, ENS Paris-Saclay, Apr – Jun) will work on unsupervised learning on graphs.
    • Ivan Conjeaud (M2 PSE, Jan – Jun) will work on a game theoretic problem on graphs.
    • Gaspard Abel (M1 Economics, ENS Paris-Saclay, Feb – July) will work on competitive diffusion processes.
    • Haytham Borchani (M1 ENSTA Paris, May – August) will work on interpretable ML.
  • AI Cup: Last days for registering to the Franco-Bavarian AI Cup that we enthousiastically co-organize with University of Passau, Bavaria, Germany.
  • Workshop poster: Harry Sevi presented our joint work with a poster at the Workshop on Recent Advancements on Graph Machine Learning of Sorbonne University.
  • Preprint: A new preprint Generalized Spectral Clustering for Directed and Undirected Graphs, co-authored with H. Sevi and M. Jonckeere can be found at [arxiv page].
  • Preprint: The preprint Online non-parametric change-point detection for heterogeneous data streams observed over graph nodes, co-authored with A. de la Concha and Nicolas Vayatis can be found at [arxiv page].
  • New intern – Gaspard Abel (M1 Economics, ENS Paris-Saclay) will work on competition in epidemic systems.
  • JMLR: The article “Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation“, co-authored by P. Humbert, B. Le Bars, L. Oudre, A. Kalogeratos, and N. Vayatis, has been accepted to the Journal of Machine Learning Research (JMLR, impact factor: 5.2), 2021. The paper comes with a python package that implements the proposed method. [pdf][bib][code]
  • Preprint: A new review paper “Epidemic Models for COVID-19 during the First Wave from February to May 2020: a Methodological Review“, co-authored by M. Garin, M. Limnios, A. Nicolaï, I. Bargiotas, O. Boulant, S.E. Chick, A. Dib, T. Evgeniou, M. Fekom, A. Kalogeratos, C. Labourdette, A. Ovchinnikov, R. Porcher, C. Pouchol, and N. Vayatis. This is an important collaborative study conducted by members or Centre Borelli and other collaborators and colleagues during the last period. [pdf]
  • Summer-school: Time has come for this year’s French-German Summer-school that I am gladly co-organizing with folks and colleagues from Academia and Industry.
  • New interns:
    • Two new L3 students from Maths ENS Paris-Saclay, Timothé Chambéry and Alexandre Surin will be working with us on graph-theoretic problems. Moreover,
    • Frédéric Zheng (M1 Mines-Paristech) will work on ensemble learning, and Martin Graive (M2 MVA) will work on epidemics in micro-communities.
  • AISTATS 2021: The paper Offline detection of change-points in the mean for stationary graph signals, co-authored with A. de la Concha and N. Vayatis will appear in the 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021) – 455/1527 submissions were accepted (29.8% rate) [pdf][appendix][code][poster]
  • PLoS ONE: The paper Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning, co-authored with I. Bargiotas, M. Limnios, P.–P. Vidal, D. Ricard, and N. Vayatis, was accepted to the PLoS ONE journal. [older tech report: pdf, and the final version will become available soon]
  • PhD defenses: Three of our students that I gladly collaborated for several years are defending their PhDs next days. Mathilde Fekom (21/1), Pierre Humbert (22/1), and Batiste Le Bars (29/1). Good luck with reaching the final line guys!!
  • New team member: It’s a great pleasure that Harry Sevi joined the MLMDA research group. His postdoc position will be funded by the Chair AI and it will be great that we will have the opportunity to work closely together on subjects related to ML and Graphs, as well as on industrial applications.
  • Blog page: Here’s a new blog page with posts around and beyond technical matters that do matter.
  • Preprint: Efficient stream-based Max-Min diversification with minimal failure rate, co-authored with Mathilde Fekom [pdf].
  • New intern: I welcome with pleasure our new intern: Ivan Conjeaud (M1 ENS Economics and Parcour AI) will work on competitive epidemics with application to panic buying, trend diffusion, etc.
  • Workshop: Proud co-organizers of the Digital French-German Summer School with Industry 2020! Several works of our team will be presented in this event!
  • Preprint: Winning the competition: enhancing counter-contagion in SIS-like epidemic processes, co-authored with S. S. Mannelli [pdf]
  • Preprint: “Model family selection for classification using Neural Decision Trees” co-authored with A. Mérida and M. Mougeot [pdf]
  • Preprint – “Offline detection of change-points in the mean for stationary graph signals” co-authored with A. de la Concha and N. Vayatis [pdf]
  • Follow-up: The paper “Dynamic Epidemic Control via Sequential Resource Allocation” co-authored with M. Fekom and N. Vayatis, is the finalization of the previous work published at CDC 2019 [pdf].
  • ICML 2020: The paper “Learning the piece-wise constant graph structure of a varying Ising model” co-authored with B. Le Bars, P. Humbert, and N. Vayatis, will appear in the International Conference on Machine Learning 2020 [pdf: a previous version, the final will be out soon].
  • ONADAP project: a newly funded research project/collaboration that will try to produce practical solutions for hospital monitoring and decision making during a period such as the recent pandemic. Centre Borelli and the MLMDA team have central role in this project.
  • New interns: I welcome with great pleasure our new interns:
    • Randa Elmrabet Tarmach (M2 MVA) will work on unsupervised statistical learning;
    • Kais Cheikh (M1 ENSTA) will work on budget(ed) learning;
    • Mohamed El Khames BOUMAIZA (M1 ENSTA) will work on change-points detection in network streams;
    • Wendong Liang and Baptiste Loreau (L3 Maths ENS Paris-Saclay) will work on the intersection of topological data analysis and graph theory;
    • Martin Dhaussy (L3 Economics ENS Paris-Saclay) will work graph robustification;
    • Aaron MAMANN (M1)… on epidemic signal processing.
  • New PhD with scholarship: Our PhD project proposal with the title “Towards Interpretable and Versatile Machine Learning” for the candidate Anthea Mérida (supervised by M. Mougeot and me) was ranked 1st in the DIM MathInnov of Paris Region PhD 2020.
  • COVID-19 epidemic: A new web page was posted hosting results from our lab and resources from the research community.
  • Preprint: Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation. P. Humbert, B. Le Bars, L. Oudre, A. Kalogeratos, and N. Vayatis, Technical Report, Nov 2019. [pdf]
  • Centre Giovanni Borelli: Since the 1st of January 2020, the Centre de Mathématiques et de Leurs Applications (CMLA) of the ENS Paris-Saclay and the research team CognacG of the University Paris Centre have formed the Center Giovanni Borelli (Unité Mixte de Recherche : UMR 9010).
  • Preprint: A new paper was released, as technical report, entitled “Detecting multiple change-points in the time-varying Ising model“. The paper is co-authored with B. Le Bars, P. Humbert, and N. Vayatis, Oct 2019. [pdf][arXiv link]
  • ICTAI 2019: Optimal Multiple Stopping Rule for Warm-Starting Sequential Selection, co-authored with Mathilde Fekom and Nicolas Vayatis, will appear in the IEEE International Conference on Tools with Artificial Intelligence (ICTAI), to be held at Portland, Oregon, US, on Nov. 4 – 6, 2019. [pdf][arxiv link]
  • CDC 2019: “Sequential Dynamic Resource Allocation for Epidemic Control“, co-authored with Mathilde Fekom and Nicolas Vayatis, will appear in the IEEE Conference on Decision and Control 2019 (CDC), to be held at Nice, France, on Dec. 11 – 13, 2019. [pdf][arxiv link]
  • Preprint: A new paper was released, as technical report, entitled
    “Revealing posturographic features associated with the risk of falling in patients with Parkinsonian syndromes via machine learning”. The paper is co-authored with I. Bargiotas, M. Limnios, P.–P. Vidal, D. Ricard, and N. Vayatis, July 2018. [pdf][arXiv link]
  • Workshop Talk: Mathilde Fekom will present our work (joint work with me and N. Vayatis) on the “Warm-starting Sequential Selection Problem“ at the 7th International Workshop in Sequential Methodologies 2019 (IWSM), Jun 18 – 21, 2019, State University of New York at Binghamton, US.
  • New PhD student: Congratulations to Alejandro David De La Concha Duarte, who is currently doing his MVA Master internship with us, and has been selected as MathInnov PhD laureate 2019-2022 to do his PhD on our research proposal on Machine Learning on Networks (supervisors: A. Kalogeratos, N. Vayatis).
  • Dataset release: The Sigfox dataset is released, containing communication activity recorded in a real IoT network.
  • New interns:
    • Alejandro de la Concha (M2 MVA, Apr – Sep) will work on multivariate signal segmentation.
    • Anthea Mérida (M2, Apr – Oct) will work on ensemble methods and random forests.
    • Amel Addala (M2, Mar – Aug) will work on a problem related to EDF’s power network.
    • Rafael Gromit and Blandine Galiay (L3 ENS Paris-Saclay, Apr – Jul) will work on sequential selection processes over graphs.
    • Vincent Laheurte and Ferdinand Campos (L3 ENS Paris-Saclay, Apr – Jul) will work on statistical homogeneity testing.
  • ICASSP 2019: “Learning Laplacian Matrix from Bandlimited Graph Signals“, co-authored with Batiste Le Bars, Pierre Humbert, and Laurent Oudre, will appear in the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 12-17 May, 2019, Brighton, UK. [pdf available soon]
  • INFOCOM 2019: “A Probabilistic Framework to Node-level Anomaly Detection in Communication Networks“, co-authored with Batiste Le Bars, will appear in the IEEE International Conference on Computer Communications 2019 (INFOCOM), 29 Apr – 2 May 2019, Paris, France. [288 papers accepted / 1464 submissions: 19.7% rate] [pdf][bib]
  • Preprint: A new paper was released, as Technical Report, introducing and analyzing the “The Multi-Round Sequential Selection Problem“. It is co-authored with M. Fekom, and N. Vayatis, September 2018. [pdf][arXiv link]
  • Book Chapter: Information Diffusion and Rumor Spreading, A. Kalogeratos, K. Scaman, L. Corinzia, and N. Vayatis, chapter in the book Cooperative and Graph Signal Processing – Principles and Applications, eds. P.M. Djuric and C. Richard, Elsevier, 2018. [pdf][publisher link][bib]
  • Preprint: A short paper with preliminary results, entitled “Node-level Anomaly Detection in Communication Networks“, co-authored with Batiste Le Bars, will be presented on June at the 3rd Graph Signal Processing Workshop (GSP), 2018.
  • Workshop Poster: Part of our work with Mathilde Fekom on sequential selection processes will be presented as a poster will be presented at the Workshop on Multi-Armed Bandits and Learning Algorithms.
  • Workshop Talk: On the French German summer school on Transfer Learning, June 4-6 2018, ENS-Paris-Saclay.
  • New intern: Thales Loiola Raveli will be working on the modeling of transportation traffic (May – Aug 2018).
  • TechReport: A new paper was released as Technical Report. Its title is A Spectral Method for Activity Shaping in Continuous-Time Information Cascades and it is co-authored with K. Scaman, L. Corinzia, and N. Vayatis, Sep 15, 2017. [pdf][arXiv link]
  • New PhD student: Mathilde Fekom, previously a Master student at CMLA, will continue with us to the PhD adventure (starting Sep. 2017), after obtaining a highly competitive scholarship from Université Paris Saclay.
  • New students: We welcome three new students in the ML on Networks theme of MLMDA group, Mathilde Fekom (MSc thesis), Matteo Neri (MSc thesis), and Marin Scalbert (MSc internship), that are going to be with us at CMLA this semester.
  • Invited Talk: A two-hours seminar talk on “Epidemics, Competition and Resource Management” was given in Paris at a Working Group on Machine Learning and Big Data of the French Ministry of Social Affairs and Health (organizer: Magali Beffy). The group is formed by scientists and researchers working on various organizations/institutions (Ministry of Health, INSEE, IRDES, Dauphine) – 25/1/2017.
  • MECO 2017: Part of the ongoing work on behavioral epidemics and dynamic control done with Stefano Sarao, Kevin Scaman, and Nicolas Vayatis is going to be presented in a poster format by Stefano at the 42nd Middle European Cooperation in Statistical Physics (MECO), Feb 2017, Lyon, France.
  • ΑΑΑΙ 2017: “Multivariate Hawkes Processes for Large-scale Inference“, co-authored with Rémi Lemonnier and Kevin Scaman, will appear in the 31st AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, CA, US. [638 papers accepted / 2,590 submissions : 24.63% rate] – [pdf][supplementary][poster].
  • PhD jury member: Kevin Scaman successfully defended in October his PhD thesis at CMLA, ENS Cachan. I am glad that I have been co-supervisor and collaborator to Kevin for three years, and finally a jury member in his defense.
  • MORANE project: The project that I will be primarily been involved in the next year has been launched on Sep. 2016 and is in collaboration with SNCF, the French National Railway Company (read more).
  • CCS 2016: Part of our work with Stefano Sarao, Kevin Scaman, and Nicolas Vayatis, appeared at the Conference on Complex Systems 2016 at Amsterdam as a full oral presentation entitled “Dynamic control of social diffusion using extensions of the SIS model” (on a working paper).
  • PC Member: 2nd International Workshop on “Data Science for Social Media and Risk“, part of IEEE ICDM 2016.
  • TNSE journal: Suppressing Epidemics in Networks using Priority-Planning, co-authored with K. Scaman, and N. Vayatis, published in IEEE Transactions on Network Science and Engineering (TNSE) [pdf][bib].
  • Invited Talk: “Dynamic suppression of epidemics on networks“, at the Complex Networks research group of LIP6, Paris 6 (Jussieu), France, 13/6/2016.
  • Invited Talk: “Epidemics in the new socio-economic era: challenges and applications“, at the Department of Computer Science and Engineering, University of Ioannina, Greece, 25/5/2016.
  • Invited Talk: “Suppressing epidemics on arbitrary networks using treatment resources of limited efficiency“, at INRA Research Center at Jouy-en-Josas, Paris area, 4/3/2016.
  • Preprint: A technical report under the title Multivariate Hawkes Processes for Large-Scale Inference, co-authored with R. Lemonnier and K. Scaman was released, Feb 26, 2016. [arXiv link][pdf][bib].
  • SETN 2016: Accepted paper Improving Text Stream Clustering using Term Burstiness and Co-burstiness, co-authored with P. Zagorisios and A. Likas, at the Hellenic Conference of Artificial Intelligence (SETN), May 18-20, 2016. [pdf][slides][bib].
  • NIPS Networks 2015: A workshop paper with the title Learning to Suppress SIS Epidemics in Networks, co-authored with K. Scaman and N. Vayatis, will appear in the “Networks in the Social and Information Sciences” workshop in conjunction with 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), November 9-12, 2015. [pdf][poster][bib].
  • ICTAI 2015: A conference paper with the title A Greedy Approach for Dynamic Control of Diffusion Processes in Networks, co-authored with K. Scaman and N. Vayatis, will appear in the IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 652-659, November 9-12, 2015. [pdf] — You can find more about this methodology in the related page.
  • FET proposal: A research proposal has been submitted on Sep 2015 for evaluation and consideration for getting funded in the frame of E.C. Horizon 2020 – Research and Innovation Framework Program.
  • Invited Summit Talk: Efficient algorithms for the suppression of diffusion processes on networks with application in epidemiology and marketing, summit: “Big data and public policies for the transportation” organized by the General Direction of Infrastructures, Transportation, and the General Commissioner on Durable Development of the Ministry of Ecology, Durable Development and Energy, along with ENS Cachan and PSE-School of Economics of Paris (15/10/2015) [agenda][presentation].