MmWave vehicular beam selection with situational awareness using machine learning Y Wang, A Klautau, M Ribero, ACK Soong, RW Heath
IEEE Access 7, 87479-87493, 2019
93 2019 Reducing communication in federated learning via efficient client sampling M Ribero, H Vikalo
Pattern Recognition 148, 110122, 2024
90 * 2024 (Nearly) Dimension Independent Private ERM with AdaGrad Rates\{via Publicly Estimated Subspaces P Kairouz, MR Diaz, K Rush, A Thakurta
Conference on Learning Theory, 2717-2746, 2021
37 * 2021 Mmwave vehicular beam training with situational awareness by machine learning Y Wang, A Klautau, M Ribero, M Narasimha, RW Heath
2018 IEEE Globecom Workshops (GC Wkshps), 1-6, 2018
34 2018 Federating recommendations using differentially private prototypes M Ribero, J Henderson, S Williamson, H Vikalo
Pattern Recognition 129, 108746, 2022
30 2022 Deep learning propagation models over irregular terrain M Ribero, RW Heath, H Vikalo, D Chizhik, RA Valenzuela
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
25 2019 Federated learning under intermittent client availability and time-varying communication constraints M Ribero, H Vikalo, G De Veciana
IEEE Journal of Selected Topics in Signal Processing 17 (1), 98-111, 2022
16 2022 A comparison of different crime prediction models for Bogotá F Barreras, C Díaz, Á Riascos, M Ribero
Documentos CEDE 34, 2016
14 2016 Comparación de diferentes modelos para la predicción del crimen en bogotá F Barreras, C Díaz, ÁJ Riascos, M Ribero
Economía y seguridad en el posconflicto, 209, 2018
10 2018 A Joint Exponential Mechanism For Differentially Private Top- J Gillenwater, M Joseph, A Munoz, MR Diaz
International Conference on Machine Learning, 7570-7582, 2022
9 2022 Easy differentially private linear regression K Amin, M Joseph, M Ribero, S Vassilvitskii
arXiv preprint arXiv:2208.07353, 2022
7 * 2022 Una comparación de diferentes modelos para la predicción del crimen en bogotá (a comparison of different crime prediction models for bogotá) F Barreras, C Diaz, A Riascos, M Ribero
Documento CEDE, 2016
2 2016 R\'enyiTester: A Variational Approach to Testing Differential Privacy W Kong, AM Medina, M Ribero
arXiv preprint arXiv:2307.05608, 2023
1 2023 A joint exponential mechanism for differentially private top-k set M Joseph, J Gillenwater, M Ribero
NeurIPS 2021 Workshop Privacy in Machine Learning, 2021
1 2021 Improving transparency of the Colombian Peace Treaty with NLP F Barreras, M Ribero, F Suárez
Quantil Documentos de Trabajo, 2017
1 2017 DP-SGD for non-decomposable objective functions W Kong, AM Medina, M Ribero
arXiv preprint arXiv:2310.03104, 2023
2023 Una comparación de diferentes modelos para la predicción del crimen en Bogotá F Barreras, C Díaz, ÁJR Villegas, M Ribero
2016 