| Statistical guarantees for regularized neural networks M Taheri, F Xie, J Lederer Neural Networks 142, 148-161, 2021 | 31 | 2021 |
| A self-adaptive local metric learning method for classification M Taheri, Z Moslehi, A Mirzaei, M Safayani Pattern Recognition 96, 106994, 2019 | 15 | 2019 |
| Balancing statistical and computational precision and applications to penalized linear regression with group sparsity M Taheri, N Lim, J Lederer Department of Computer Sciences and Department of Biostatistics and Medical …, 2016 | 11 | 2016 |
| Discriminative fuzzy c-means as a large margin unsupervised metric learning algorithm Z Moslehi, M Taheri, A Mirzaei, M Safayani IEEE Transactions on Fuzzy Systems 26 (6), 3534-3544, 2018 | 10 | 2018 |
| Efficient feature selection with large and high-dimensional data M Taheri, N Lim, J Lederer arXiv preprint arXiv:1609.07195, 2020 | 7 | 2020 |
| Balancing Statistical and Computational Precision: A General Theory and Applications to Sparse Regression M Taheri, N Lim, J Lederer IEEE Transactions on Information Theory 69 (1), 316-333, 2022 | 1 | 2022 |
| Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks M Taheri, F Xie, J Lederer arXiv preprint arXiv:2205.04491, 2022 | 1 | 2022 |
| How many samples are needed to train a deep-ReLU neural network? P Golestaneh, M Taheri, J Lederer | | 2023 |
| Statistical guarantees for regularized (approximate) estimators in machine learning M Taheri | | 2023 |
