| A novel approach to quantized matrix completion using huber loss measure A Esmaeili, F Marvasti IEEE Signal Processing Letters 26 (2), 337-341, 2019 | 37 | 2019 |
| Cnll: A semi-supervised approach for continual noisy label learning N Karim, U Khalid, A Esmaeili, N Rahnavard Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 21 | 2022 |
| Select to better learn: Fast and accurate deep learning using data selection from nonlinear manifolds M Joneidi, S Vahidian, A Esmaeili, W Wang, N Rahnavard, B Lin, M Shah Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 19 | 2020 |
| Iterative null space projection method with adaptive thresholding in sparse signal recovery A Esmaeili, EA Kangarshahi, F Marvasti IET Signal Processing 12 (5), 605-612, 2018 | 19* | 2018 |
| Transductive multi-label learning from missing data using smoothed rank function A Esmaeili, K Behdin, MA Fakharian, F Marvasti Pattern Analysis and Applications 23, 1225-1233, 2020 | 15* | 2020 |
| Missing low-rank and sparse decomposition based on smoothed nuclear norm M Azghani, A Esmaeili, K Behdin, F Marvasti IEEE Transactions on Circuits and Systems for Video Technology 30 (6), 1550-1558, 2019 | 13 | 2019 |
| Obtain: Real-time beat tracking in audio signals A Mottaghi, K Behdin, A Esmaeili, M Heydari, F Marvasti arXiv preprint arXiv:1704.02216, 2017 | 13 | 2017 |
| Rodd: A self-supervised approach for robust out-of-distribution detection U Khalid, A Esmaeili, N Karim, N Rahnavard 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2022 | 12 | 2022 |
| Two-way Spectrum Pursuit for CUR Decomposition and Its Application in Joint Column/Row Subset Selection A Esmaeili, M Joneidi, M Salimitari, U Khalid, N Rahnavard Machine Learning for Signal Processing - MLSP 2021, 2021 | 9 | 2021 |
| Comparison of several sparse recovery methods for low rank matrices with random samples A Esmaeili, F Marvasti 2016 8th International Symposium on Telecommunications (IST), 191-195, 2016 | 9 | 2016 |
| Low-rank and sparse decomposition for low-query decision-based adversarial attacks A Esmaeili, M Edraki, N Rahnavard, A Mian, M Shah IEEE Transactions on Information Forensics and Security 19, 1561-1575, 2023 | 7* | 2023 |
| Using empirical covariance matrix in enhancing prediction accuracy of linear models with missing information A Moradipari, S Shahsavari, A Esmaeili, F Marvasti 2017 International conference on sampling theory and applications (SampTA …, 2017 | 6 | 2017 |
| Fast methods for recovering sparse parameters in linear low rank models A Esmaeili, A Amini, F Marvasti 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016 | 6 | 2016 |
| Spectrum pursuit with residual descent for column subset selection problem: Theoretical guarantees and applications in deep learning S Vahidian, M Joneidi, A Esmaeili, S Khodadadeh, S Zehtabian, B Lin IEEE Access 10, 88164-88177, 2022 | 4 | 2022 |
| Recovering quantized data with missing information using bilinear factorization and augmented Lagrangian method A Esmaeili, K Behdin, F Marvasti arXiv preprint arXiv:1810.03222, 2018 | 3 | 2018 |
| A Novel Approach to Sparse Inverse Covariance Estimation Using Transform Domain Updates and Exponentially Adaptive Thresholding A Esmaeili, F Marvasti arXiv preprint arXiv:1811.06773, 2018 | 1 | 2018 |
| Rodd: A self-supervised approach for robust out-of-distribution detection. In 2022 IEEE U Khalid, A Esmaeili, N Karim, N Rahnavard CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW …, 0 | | |
farokh marvastiSharif University of Technology, EE and ACRIDirección de correo verificada de sharif.edu
