Argyris Kalogeratos

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Nicolas VayatisProfesseur des universités, ENS Paris-SaclayVerified email at ens-paris-saclay.fr
Aristidis LikasProfessor, Computer Science & Engineering, University of Ioannina, GreeceVerified email at cs.uoi.gr
Kevin ScamanResearch scientist, INRIAVerified email at inria.fr
Batiste Le BarsPostdoctoral researcher, Inria Lille - Magnet teamVerified email at inria.fr
Vasileios ChasanisUniversity of IoanninaVerified email at cs.uoi.gr
Ioannis BargiotasCentre Borelli - École Normale Supérieure Paris-SaclayVerified email at ens-paris-saclay.fr
Myrto LimniosPostdoc @ Statistics and Probability Theory, MATH Department, University of CopenhagenVerified email at math.ku.dk
Laurent OudreProfessor, Centre Borelli, ENS Paris-SaclayVerified email at ens-paris-saclay.fr
Pierre-Paul VIDALCNRSVerified email at parisdescartes.fr
Luca CorinziaPostdoc in Machine Learning, ETH ZurichVerified email at ethz.ch
Remi LemonnierPhD Student, CMLA, ENS CachanVerified email at ens-cachan.fr
Theodoros EvgeniouINSEADVerified email at insead.edu
Anton OvchinnikovQueen's School of BusinessVerified email at queensu.ca
Amir DibUniversité Paris-Saclay, CNRS, ENS Paris-Saclay, Centre BorelliVerified email at ens-paris-saclay.fr
Stephen E. ChickProfessor of Technology and Operations Management, INSEADVerified email at insead.edu
Mathilde MougeotProfessor ENSIIEVerified email at ensiie.fr
Zoran BabovicInnovation Center of the School of Electrical Engineering, University of Belgrade & Faculty ofVerified email at etf.rs
Harry SeviENS Paris-SaclayVerified email at ens-paris-saclay.fr
Stefano SARAO MANNELLIGatsby Computational Neuroscience Unit & Sainsbury Wellcome Centre | University College LondonVerified email at ucl.ac.uk

Argyris Kalogeratos

Researcher at Centre Borelli, ENS Paris-Saclay

Verified email at ens-paris-saclay.fr - Homepage

Machine Learning Artificial Intelligence Complex Networks


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Dip-means: an incremental clustering method for estimating the number of clusters A Kalogeratos, A Likas Advances in neural information processing systems 25, 2012	91	2012
Text document clustering using global term context vectors A Kalogeratos, A Likas Knowledge and information systems 31 (3), 455-474, 2012	51	2012
Movie segmentation into scenes and chapters using locally weighted bag of visual words V Chasanis, A Kalogeratos, A Likas Proceedings of the ACM International Conference on Image and Video Retrieval …, 2009	48	2009
Document clustering using synthetic cluster prototypes A Kalogeratos, A Likas Data & Knowledge Engineering 70 (3), 284-306, 2011	43	2011
Multivariate Hawkes processes for large-scale inference R Lemonnier, K Scaman, A Kalogeratos Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017	32	2017
Suppressing epidemics in networks using priority planning K Scaman, A Kalogeratos, N Vayatis IEEE Transactions on Network Science and Engineering 3 (4), 271-285, 2016	24	2016
Learning Laplacian matrix from bandlimited graph signals B Le Bars, P Humbert, L Oudre, A Kalogeratos ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019	21	2019
A probabilistic framework to node-level anomaly detection in communication networks B Le Bars, A Kalogeratos IEEE INFOCOM 2019-IEEE Conference on Computer Communications, 2188-2196, 2019	14	2019
A greedy approach for dynamic control of diffusion processes in networks K Scaman, A Kalogeratos, N Vayatis 2015 IEEE 27th International Conference on Tools with Artificial …, 2015	14	2015
Improving text stream clustering using term burstiness and co-burstiness A Kalogeratos, P Zagorisios, A Likas Proceedings of the 9th hellenic conference on artificial intelligence, 1-9, 2016	11	2016
Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning I Bargiotas, A Kalogeratos, M Limnios, PP Vidal, D Ricard, N Vayatis Plos one 16 (2), e0246790, 2021	6	2021
Learning the piece-wise constant graph structure of a varying ising model B Le Bars, P Humbert, A Kalogeratos, N Vayatis International Conference on Machine Learning, 675-684, 2020	6	2020
Dynamic treatment allocation for epidemic control in arbitrary networks K Scaman, A Kalogeratos, N Vayatis Diffusion Networks and Cascade Analytics workshop, 2014	6	2014
What makes a good plan? An efficient planning approach to control diffusion processes in networks K Scaman, A Kalogeratos, N Vayatis arXiv preprint arXiv:1407.4760, 2014	5	2014
Sequential dynamic resource allocation for epidemic control M Fekom, N Vayatis, A Kalogeratos 2019 IEEE 58th Conference on Decision and Control (CDC), 6338-6343, 2019	4	2019
Information diffusion and rumor spreading A Kalogeratos, K Scaman, L Corinzia, N Vayatis Cooperative and Graph Signal Processing, 651-678, 2018	4	2018
A spectral method for activity shaping in continuous-time information cascades K Scaman, A Kalogeratos, L Corinzia, N Vayatis arXiv preprint arXiv:1709.05231, 2017	4	2017
Learning to suppress SIS epidemics in networks A Kalogeratos, K Scaman, N Vayatis Networks in the Social and Information Sciences workshop, 2015	4	2015
Learning laplacian matrix from graph signals with sparse spectral representation P Humbert, B Le Bars, L Oudre, A Kalogeratos, N Vayatis Journal of Machine Learning Research, 2021	3	2021
Epidemic models for covid-19 during the first wave from February to May 2020: A methodological review M Garin, M Limnios, A Nicolaï, I Bargiotas, O Boulant, SE Chick, A Dib, ... medRxiv, 2021	3	2021

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