| Dinov2: Learning robust visual features without supervision M Oquab, T Darcet, T Moutakanni, H Vo, M Szafraniec, V Khalidov, ... arXiv preprint arXiv:2304.07193, 2023 | 1855 | 2023 |
| Distributed optimization in sensor networks M Rabbat, R Nowak Proceedings of the 3rd international symposium on Information processing in …, 2004 | 1094 | 2004 |
| Gossip algorithms for distributed signal processing AG Dimakis, S Kar, JMF Moura, MG Rabbat, A Scaglione Proceedings of the IEEE 98 (11), 1847-1864, 2010 | 1030 | 2010 |
| fastMRI: An open dataset and benchmarks for accelerated MRI J Zbontar, F Knoll, A Sriram, T Murrell, Z Huang, MJ Muckley, A Defazio, ... arXiv preprint arXiv:1811.08839, 2018 | 925 | 2018 |
| Compressed sensing for networked data J Haupt, WU Bajwa, M Rabbat, R Nowak IEEE Signal Processing Magazine 25 (2), 92-101, 2008 | 721 | 2008 |
| How land-use and urban form impact bicycle flows: Evidence from the bicycle-sharing system (BIXI) in Montreal A Faghih-Imani, N Eluru, AM El-Geneidy, M Rabbat, U Haq Journal of transport geography 41, 306-314, 2014 | 615 | 2014 |
| Network topology and communication-computation tradeoffs in decentralized optimization A Nedić, A Olshevsky, MG Rabbat Proceedings of the IEEE 106 (5), 953-976, 2018 | 606 | 2018 |
| Sustainable ai: Environmental implications, challenges and opportunities CJ Wu, R Raghavendra, U Gupta, B Acun, N Ardalani, K Maeng, G Chang, ... Proceedings of Machine Learning and Systems 4, 795-813, 2022 | 499 | 2022 |
| Learning graphs from data: A signal representation perspective X Dong, D Thanou, M Rabbat, P Frossard IEEE Signal Processing Magazine 36 (3), 44-63, 2019 | 466 | 2019 |
| Tarmac: Targeted multi-agent communication A Das, T Gervet, J Romoff, D Batra, D Parikh, M Rabbat, J Pineau International Conference on machine learning, 1538-1546, 2019 | 454 | 2019 |
| Quantized incremental algorithms for distributed optimization MG Rabbat, RD Nowak IEEE Journal on Selected Areas in Communications 23 (4), 798-808, 2005 | 443 | 2005 |
| Stochastic gradient push for distributed deep learning M Assran, N Loizou, N Ballas, M Rabbat International Conference on Machine Learning, 344-353, 2019 | 408 | 2019 |
| fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ... Radiology: Artificial Intelligence 2 (1), e190007, 2020 | 398 | 2020 |
| Push-sum distributed dual averaging for convex optimization KI Tsianos, S Lawlor, MG Rabbat 2012 ieee 51st ieee conference on decision and control (cdc), 5453-5458, 2012 | 356 | 2012 |
| Distributed average consensus with dithered quantization TC Aysal, MJ Coates, MG Rabbat IEEE transactions on Signal Processing 56 (10), 4905-4918, 2008 | 347 | 2008 |
| Masked siamese networks for label-efficient learning M Assran, M Caron, I Misra, P Bojanowski, F Bordes, P Vincent, A Joulin, ... European Conference on Computer Vision, 456-473, 2022 | 336 | 2022 |
| Federated learning with buffered asynchronous aggregation J Nguyen, K Malik, H Zhan, A Yousefpour, M Rabbat, M Malek, D Huba International Conference on Artificial Intelligence and Statistics, 3581-3607, 2022 | 306 | 2022 |
| Self-supervised learning from images with a joint-embedding predictive architecture M Assran, Q Duval, I Misra, P Bojanowski, P Vincent, M Rabbat, Y LeCun, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 289 | 2023 |
| Decentralized source localization and tracking [wireless sensor networks] MG Rabbat, RD Nowak 2004 IEEE International Conference on Acoustics, Speech, and Signal …, 2004 | 274 | 2004 |
| Consensus-based distributed optimization: Practical issues and applications in large-scale machine learning KI Tsianos, S Lawlor, MG Rabbat 2012 50th annual allerton conference on communication, control, and …, 2012 | 270 | 2012 |
Mark CoatesProfessor of Electrical Engineering, McGill Universityece.mcgill.ca의 이메일 확인됨
