| Learning deep networks from noisy labels with dropout regularization I Jindal, M Nokleby, X Chen 2016 IEEE 16th International Conference on Data Mining (ICDM), 967-972, 2016 | 241 | 2016 |
| A unified neural network approach for estimating travel time and distance for a taxi trip I Jindal, X Chen, M Nokleby, J Ye arXiv preprint arXiv:1710.04350, 2017 | 101 | 2017 |
| Optimizing taxi carpool policies via reinforcement learning and spatio-temporal mining I Jindal, ZT Qin, X Chen, M Nokleby, J Ye 2018 IEEE International Conference on Big Data (Big Data), 1417-1426, 2018 | 74 | 2018 |
| User cooperation for energy-efficient cellular communications M Nokleby, B Aazhang 2010 IEEE International Conference on Communications, 1-5, 2010 | 66 | 2010 |
| An effective label noise model for dnn text classification I Jindal, D Pressel, B Lester, M Nokleby arXiv preprint arXiv:1903.07507, 2019 | 55 | 2019 |
| Anytime minibatch: Exploiting stragglers in online distributed optimization N Ferdinand, H Al-Lawati, SC Draper, M Nokleby arXiv preprint arXiv:2006.05752, 2020 | 48 | 2020 |
| Lattice coding over the relay channel M Nokleby, B Aazhang 2011 IEEE International Conference on Communications (ICC), 1-5, 2011 | 30 | 2011 |
| Cooperative power scheduling for wireless MIMO networks M Nokleby, AL Swindlehurst, Y Rong, Y Hua IEEE GLOBECOM 2007-IEEE Global Telecommunications Conference, 2982-2986, 2007 | 29 | 2007 |
| A robotic recording and playback platform for training surgeons and learning autonomous behaviors using the da Vinci surgical system A Pandya, S Eslamian, H Ying, M Nokleby, LA Reisner Robotics 8 (1), 9, 2019 | 28 | 2019 |
| Bargaining and the MISO interference channel M Nokleby, AL Swindlehurst EURASIP Journal on Advances in Signal Processing 2009, 1-13, 2009 | 27 | 2009 |
| Discrimination on the Grassmann manifold: Fundamental limits of subspace classifiers M Nokleby, M Rodrigues, R Calderbank IEEE Transactions on Information Theory 61 (4), 2133-2147, 2015 | 26 | 2015 |
| Toward resource-optimal consensus over the wireless medium M Nokleby, WU Bajwa, R Calderbank, B Aazhang IEEE Journal of Selected Topics in Signal Processing 7 (2), 284-295, 2013 | 24 | 2013 |
| Scaling-up distributed processing of data streams for machine learning M Nokleby, H Raja, WU Bajwa Proceedings of the IEEE 108 (11), 1984-2012, 2020 | 23 | 2020 |
| Cooperative compute-and-forward M Nokleby, B Aazhang IEEE Transactions on Wireless Communications 15 (1), 14-27, 2015 | 22 | 2015 |
| Low-density lattice codes for full-duplex relay channels NS Ferdinand, M Nokleby, B Aazhang IEEE Transactions on Wireless Communications 14 (4), 2309-2321, 2014 | 21 | 2014 |
| Deep reinforcement learning for optimizing carpooling policies I Jindal, Z Qin, X Chen, M Nokleby, J Ye US Patent App. 15/970,425, 2019 | 20 | 2019 |
| Low-dimensional shaping for high-dimensional lattice codes NS Ferdinand, BM Kurkoski, M Nokleby, B Aazhang IEEE Transactions on Wireless Communications 15 (11), 7405-7418, 2016 | 20 | 2016 |
| Stochastic optimization from distributed streaming data in rate-limited networks M Nokleby, WU Bajwa IEEE transactions on signal and information processing over networks 5 (1 …, 2018 | 14 | 2018 |
| Multi-scale spectrum sensing in dense multi-cell cognitive networks N Michelusi, M Nokleby, U Mitra, R Calderbank IEEE Transactions on Communications 67 (4), 2673-2688, 2018 | 13 | 2018 |
| “Stream loss”: ConvNet learning for face verification using unlabeled videos in the wild E Rashedi, E Barati, M Nokleby, X Chen Neurocomputing 329, 311-319, 2019 | 12 | 2019 |
Ishan JindalSamsung ResearchPatvirtintas el. paštas wayne.edu
