Distributed optimization in sensor networks M Rabbat, R Nowak Proceedings of the 3rd international symposium on Information processing in …, 2004 | 1070 | 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 | 1012 | 2010 |
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 | 862 | 2023 |
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 | 792 | 2018 |
Compressed sensing for networked data J Haupt, WU Bajwa, M Rabbat, R Nowak IEEE Signal Processing Magazine 25 (2), 92-101, 2008 | 714 | 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 | 573 | 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 | 560 | 2018 |
Quantized incremental algorithms for distributed optimization MG Rabbat, RD Nowak IEEE Journal on Selected Areas in Communications 23 (4), 798-808, 2005 | 438 | 2005 |
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 | 428 | 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 | 397 | 2019 |
Stochastic gradient push for distributed deep learning M Assran, N Loizou, N Ballas, M Rabbat International Conference on Machine Learning, 344-353, 2019 | 371 | 2019 |
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 | 342 | 2012 |
Distributed average consensus with dithered quantization TC Aysal, MJ Coates, MG Rabbat IEEE transactions on Signal Processing 56 (10), 4905-4918, 2008 | 337 | 2008 |
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 | 320 | 2020 |
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 | 304 | 2022 |
Decentralized source localization and tracking [wireless sensor networks] MG Rabbat, RD Nowak 2004 IEEE International Conference on Acoustics, Speech, and Signal …, 2004 | 271 | 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 | 257 | 2012 |
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 | 231 | 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 | 224 | 2022 |
Decentralized compression and predistribution via randomized gossiping M Rabbat, J Haupt, A Singh, R Nowak Proceedings of the 5th international conference on Information processing in …, 2006 | 208 | 2006 |