| Precise Error Analysis of Regularized -Estimators in High Dimensions C Thrampoulidis, E Abbasi, B Hassibi IEEE Transactions on Information Theory 64 (8), 5592-5628, 2018 | 280 | 2018 |
| Regularized linear regression: A precise analysis of the estimation error C Thrampoulidis, S Oymak, B Hassibi Conference on Learning Theory, 1683-1709, 2015 | 239* | 2015 |
| A model of double descent for high-dimensional binary linear classification Z Deng, A Kammoun, C Thrampoulidis Information and Inference: A Journal of the IMA 11 (2), 435-495, 2022 | 191 | 2022 |
| The squared-error of generalized lasso: A precise analysis S Oymak, C Thrampoulidis, B Hassibi 2013 51st Annual Allerton Conference on Communication, Control, and …, 2013 | 150 | 2013 |
| Optimal placement of distributed energy storage in power networks C Thrampoulidis, S Bose, B Hassibi IEEE Transactions on Automatic Control 61 (2), 416-429, 2015 | 126 | 2015 |
| Lasso with non-linear measurements is equivalent to one with linear measurements C Thrampoulidis, E Abbasi, B Hassibi Advances in Neural Information Processing Systems 28, 2015 | 124 | 2015 |
| Linear stochastic bandits under safety constraints S Amani, M Alizadeh, C Thrampoulidis Advances in Neural Information Processing Systems, 9256-9266, 2019 | 123 | 2019 |
| Label-imbalanced and group-sensitive classification under overparameterization GR Kini, O Paraskevas, S Oymak, C Thrampoulidis Advances in Neural Information Processing Systems 34, 18970-18983, 2021 | 92 | 2021 |
| Revealing hidden scenes by photon-efficient occlusion-based opportunistic active imaging F Xu, G Shulkind, C Thrampoulidis, JH Shapiro, A Torralba, FNC Wong, ... Optics express 26 (8), 9945-9962, 2018 | 89 | 2018 |
| Exploiting occlusion in non-line-of-sight active imaging C Thrampoulidis, G Shulkind, F Xu, WT Freeman, JH Shapiro, A Torralba, ... IEEE Transactions on Computational Imaging 4 (3), 419-431, 2018 | 84 | 2018 |
| Using unknown occluders to recover hidden scenes AB Yedidia, M Baradad, C Thrampoulidis, WT Freeman, GW Wornell Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 73 | 2019 |
| Analytic study of double descent in binary classification: The impact of loss GR Kini, C Thrampoulidis 2020 IEEE International Symposium on Information Theory (ISIT), 2527-2532, 2020 | 72 | 2020 |
| Fednest: Federated bilevel, minimax, and compositional optimization DA Tarzanagh, M Li, C Thrampoulidis, S Oymak International Conference on Machine Learning, 21146-21179, 2022 | 69 | 2022 |
| Symbol error rate performance of box-relaxation decoders in massive mimo C Thrampoulidis, W Xu, B Hassibi IEEE Transactions on Signal Processing 66 (13), 3377-3392, 2018 | 68 | 2018 |
| Transformers as support vector machines DA Tarzanagh, Y Li, C Thrampoulidis, S Oymak arXiv preprint arXiv:2308.16898, 2023 | 65 | 2023 |
| Imbalance trouble: Revisiting neural-collapse geometry C Thrampoulidis, GR Kini, V Vakilian, T Behnia Advances in Neural Information Processing Systems 35, 27225-27238, 2022 | 62 | 2022 |
| Autobalance: Optimized loss functions for imbalanced data M Li, X Zhang, C Thrampoulidis, J Chen, S Oymak Advances in Neural Information Processing Systems 34, 3163-3177, 2021 | 59 | 2021 |
| Benign overfitting in multiclass classification: All roads lead to interpolation K Wang, V Muthukumar, C Thrampoulidis Advances in Neural Information Processing Systems 34, 24164-24179, 2021 | 57 | 2021 |
| Provable benefits of overparameterization in model compression: From double descent to pruning neural networks X Chang, Y Li, S Oymak, C Thrampoulidis Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 6974-6983, 2021 | 57 | 2021 |
| Improved bounds on Gaussian MAC and sparse regression via Gaussian inequalities I Zadik, Y Polyanskiy, C Thrampoulidis 2019 IEEE International Symposium on Information Theory (ISIT), 430-434, 2019 | 54 | 2019 |
Babak HassibiMose and Lilian S. Bohn Professor of Electrical EngineeringVerified email at caltech.edu
