Support vector regression for link load prediction P Bermolen, D Rossi Computer Networks 53 (2), 191-201, 2009 | 144 | 2009 |
Abacus: Accurate behavioral classification of P2P-TV traffic P Bermolen, M Mellia, M Meo, D Rossi, S Valenti Computer Networks 55 (6), 1394-1411, 2011 | 90 | 2011 |
Accurate, fine-grained classification of P2P-TV applications by simply counting packets S Valenti, D Rossi, M Meo, M Mellia, P Bermolen Traffic Monitoring and Analysis: First International Workshop, TMA 2009 …, 2009 | 65 | 2009 |
Search for optimality in traffic matrix estimation: a rational approach by Cramer-Rao lower bounds P Bermolen, S Vaton, I Juva 2006 2nd Conference on Next Generation Internet Design and Engineering, 2006 …, 2006 | 32 | 2006 |
The jamming constant of uniform random graphs P Bermolen, M Jonckheere, P Moyal Stochastic Processes and their Applications 127 (7), 2138-2178, 2017 | 29 | 2017 |
Quality of service parameters and link operating point estimation based on effective bandwidths L Aspirot, P Belzarena, P Bermolen, A Ferragut, G Perera, M Simon Performance Evaluation 59 (2-3), 103-120, 2005 | 20 | 2005 |
Estimating the transmission probability in wireless networks with configuration models P Bermolen, M Jonckheere, F Larroca, P Moyal ACM Transactions on Modeling and Performance Evaluation of Computing Systems …, 2016 | 13 | 2016 |
Extremal versus additive Matérn point processes F Baccelli, P Bermolen Queueing Systems 71, 179-197, 2012 | 10 | 2012 |
Online change point detection for weighted and directed random dot product graphs B Marenco, P Bermolen, M Fiori, F Larroca, G Mateos IEEE Transactions on Signal and Information Processing over Networks 8, 144-159, 2022 | 9 | 2022 |
Estimating the spatial reuse with configuration models P Bermolen, M Jonckheere, F Larroca, P Moyal arXiv preprint arXiv:1411.0143, 2014 | 9 | 2014 |
Scaling limits and generic bounds for exploration processes P Bermolen, M Jonckheere, J Sanders Journal of Statistical Physics 169, 989-1018, 2017 | 7 | 2017 |
Change point detection in weighted and directed random Dot Product Graphs F Larroca, P Bermolen, M Fiori, G Mateos 2021 29th European Signal Processing Conference (EUSIPCO), 1810-1814, 2021 | 6 | 2021 |
Degree-greedy algorithms on large random graphs P Bermolen, M Jonckheere, F Larroca, M Saenz ACM SIGMETRICS Performance Evaluation Review 46 (3), 27-32, 2019 | 6 | 2019 |
Scaling limits for exploration algorithms P Bermolen, M Jonckheere, J Sanders arXiv preprint arXiv:1504.02438, 2015 | 6 | 2015 |
Large-scale 802.11 wireless networks data analysis based on graph clustering G Capdehourat, P Bermolen, M Fiori, N Frevenza, F Larroca, G Morales, ... Wireless Personal Communications 120, 1791-1819, 2021 | 5 | 2021 |
Network forecast with support vector machines P Bermolen, D Rossi Proceedings of the International Workshop on Traffic Management and Traffic …, 2007 | 5 | 2007 |
Ancho de banda efectivo para flujos markovianos P Bermolen UR. FING, 2003 | 5 | 2003 |
Federated learning for data analytics in education C Fachola, A Tornaría, P Bermolen, G Capdehourat, L Etcheverry, ... Data 8 (2), 43, 2023 | 4 | 2023 |
Large Deviation Principle for the Greedy Exploration Algorithm over Erd\" os-R\'enyi Graphs P Bermolen, V Goicoechea, M Jonckheere, E Mordecki arXiv preprint arXiv:2007.04753, 2020 | 4 | 2020 |
Multi-resource allocation: Analysis of a paid spectrum sharing approach based on fluid models C Rattaro, P Bermolen, P Belzarena IEEE Transactions on Cognitive Communications and Networking 4 (3), 607-617, 2018 | 4 | 2018 |