| What is being transferred in transfer learning? B Neyshabur, H Sedghi, C Zhang Neural Information Processing Systems (NeurIPS), 2020 | 445 | 2020 |
| Beating the perils of non-convexity: Guaranteed training of neural networks using tensor methods M Janzamin, H Sedghi, A Anandkumar arXiv preprint arXiv:1506.08473, 2015 | 251 | 2015 |
| The Singular Values of Convolutional Layers H Sedghi, V Gupta, PM Long arXiv preprint arXiv:1805.10408, 2018 | 214 | 2018 |
| The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks R Entezari, H Sedghi, O Saukh, B Neyshabur International Conference on Learning Representations, 2022 | 148 | 2022 |
| Leveraging Unlabeled Data to Predict Out-of-Distribution Performance S Garg, S Balakrishnan, ZC Lipton, B Neyshabur, H Sedghi International Conference on Learning Representations, 2022 | 115 | 2022 |
| Generalization bounds for deep convolutional neural networks PM Long, H Sedghi International Conference on Learning Representations, 2020 | 112* | 2020 |
| Exploring the Limits of Large Scale Pre-training S Abnar, M Dehghani, B Neyshabur, H Sedghi International Conference on Learning Representations, 2022 | 110 | 2022 |
| Provable tensor methods for learning mixtures of generalized linear models H Sedghi, M Janzamin, A Anandkumar Artificial Intelligence and Statistics, 1223-1231, 2016 | 102 | 2016 |
| Provable Methods for Training Neural Networks with Sparse Connectivity H Sedghi, A Anandkumar arXiv preprint arXiv:1412.2693, 2014 | 79 | 2014 |
| The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers P Nakkiran, B Neyshabur, H Sedghi International Conference on Learning Representations, 2021 | 70* | 2021 |
| Statistical Structure Learning to Ensure Data Integrity in Smart Grid H Sedghi, E Jonckheere IEEE Transactions on Smart Grid 6 (4), 1924-1933, 2015 | 70 | 2015 |
| Teaching Algorithmic Reasoning via In-context Learning H Zhou, A Nova, H Larochelle, A Courville, B Neyshabur, H Sedghi arXiv preprint arXiv:2211.09066, 2022 | 56 | 2022 |
| The intriguing role of module criticality in the generalization of deep networks NS Chatterji, B Neyshabur, H Sedghi International Conference on Learning Representations, 2020 | 56 | 2020 |
| REPAIR: REnormalizing Permuted Activations for Interpolation Repair K Jordan, H Sedghi, O Saukh, R Entezari, B Neyshabur ICLR 2023, 2022 | 47 | 2022 |
| Score Function Features for Discriminative Learning: Matrix and Tensor Framework M Janzamin, H Sedghi, A Anandkumar arXiv preprint arXiv:1412.2863, 2014 | 47 | 2014 |
| Statistical structure learning of smart grid for detection of false data injection H Sedghi, E Jonckheere 2013 IEEE Power & Energy Society General Meeting, 1-5, 2013 | 45 | 2013 |
| Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ... arXiv preprint arXiv:2312.06585, 2023 | 34 | 2023 |
| Sysml: The new frontier of machine learning systems A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ... | 29 | 2019 |
| A game-theoretic approach for power allocation in bidirectional cooperative communication M Janzamin, MR Pakravan, H Sedghi 2010 IEEE Wireless Communication and Networking Conference, 1-6, 2010 | 28 | 2010 |
| Size-free generalization bounds for convolutional neural networks PM Long, H Sedghi | 27 | 2019 |
Anima AnandkumarCalifornia Institute of Technology and NVIDIA在 caltech.edu 的电子邮件经过验证
