| Promises of conic relaxation for contingency-constrained optimal power flow problem R Madani, M Ashraphijuo, J Lavaei IEEE Transactions on Power Systems 31 (2), 1297-1307, 2016 | 209 | 2016 |
| Fundamental Conditions for Low-CP-Rank Tensor Completion M Ashraphijuo, X Wang Journal of Machine Learning Research (JMLR) 18 (63), 1-29, 2017 | 64 | 2017 |
| Conic relaxations of the unit commitment problem S Fattahi, M Ashraphijuo, J Lavaei, A Atamtürk Energy 134 (2017), 1079-1095, 2017 | 60 | 2017 |
| Deterministic and probabilistic conditions for finite completability of low-tucker-rank tensor M Ashraphijuo, V Aggarwal, X Wang IEEE Transactions on Information Theory 65 (9), 5380 - 5400, 2019 | 29* | 2019 |
| A Characterization of Sampling Patterns for Low-Tucker-Rank Tensor Completion Problem M Ashraphijuo, V Aggarwal, X Wang Information Theory Proceedings (ISIT), 2017 IEEE International Symposium on …, 2017 | 26 | 2017 |
| Rank determination for low-rank data completion M Ashraphijuo, X Wang, V Aggarwal Journal of Machine Learning Research (JMLR) 18 (98), 1-29, 2017 | 22 | 2017 |
| Characterization of rank-constrained feasibility problems via a finite number of convex programs M Ashraphijuo, R Madani, J Lavaei 2016 IEEE 55th Conference on Decision and Control (CDC), 6544-6550, 2016 | 21 | 2016 |
| Power system state estimation with a limited number of measurements R Madani, M Ashraphijuo, J Lavaei, R Baldick 2016 IEEE 55th conference on decision and control (CDC), 672-679, 2016 | 20 | 2016 |
| Fundamental sampling patterns for low-rank multi-view data completion M Ashraphijuo, X Wang, V Aggarwal Pattern Recognition 103 (107307), 1-24, 2020 | 19* | 2020 |
| On Deterministic Sampling Patterns for Robust Low-Rank Matrix Completion M Ashraphijuo, V Aggarwal, X Wang IEEE Signal Processing Letters 25 (3), 343-347, 2018 | 19 | 2018 |
| A Characterization of Sampling Patterns for Low-Rank Multi-View Data Completion Problem M Ashraphijuo, X Wang, V Aggarwal Information Theory Proceedings (ISIT), 2017 IEEE International Symposium on …, 2017 | 19 | 2017 |
| Characterization of sampling patterns for low-tt-rank tensor retrieval M Ashraphijuo, X Wang Annals of Mathematics and Artificial Intelligence 88 (8), 859-886, 2020 | 17* | 2020 |
| A strong semidefinite programming relaxation of the unit commitment problem M Ashraphijuo, S Fattahi, J Lavaei, A Atamtürk 2016 IEEE 55th conference on decision and control (CDC), 694-701, 2016 | 16 | 2016 |
| Clustering a union of low-rank subspaces of different dimensions with missing data M Ashraphijuo, X Wang Pattern Recognition Letters 120, 31-35, 2019 | 14 | 2019 |
| Low-rank data completion with very low sampling rate using Newton's method M Ashraphijuo, X Wang, J Zhang IEEE Transactions on Signal Processing 67 (7), 1849-1859, 2019 | 11 | 2019 |
| OPF Solver R Madani, M Ashraphijuo, J Lavaei Published online at http://www. ee. columbia. edu/~ lavaei/Software. html, 2014 | 11 | 2014 |
| An approximation of the CP-rank of a partially sampled tensor M Ashraphijuo, X Wang, V Aggarwal Allerton Conference on Communication, Control, and Computing (Allerton), 2017 | 10 | 2017 |
| Inverse function theorem for polynomial equations using semidefinite programming M Ashraphijuo, R Madani, J Lavaei Decision and Control (CDC), 2015 IEEE 54th Conference on, 6589-6596, 2015 | 10 | 2015 |
| Sdp solver of optimal power flow users manual R Madani, M Ashraphijuo, J Lavaei http://www.columbia.edu/~rm3122/OPF_Solver_Guide.pdf, 2015 | 10 | 2015 |
| Union of low-rank tensor spaces: Clustering and completion M Ashraphijuo, X Wang Journal of Machine Learning Research 21 (69), 1-36, 2020 | 9 | 2020 |