| Trained Transformers Learn Linear Models In-Context R Zhang, S Frei, PL Bartlett Journal of Machine Learning Research 25 (49), 2024 | 99 | 2024 |
| Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data S Frei, NS Chatterji, PL Bartlett Conference on Learning Theory (COLT), 2022 | 76 | 2022 |
| Agnostic Learning of a Single Neuron with Gradient Descent S Frei, Y Cao, Q Gu Advances in Neural Information Processing Systems (NeurIPS), 2020 | 63 | 2020 |
| Algorithm-dependent generalization bounds for overparameterized deep residual networks S Frei, Y Cao, Q Gu Advances in Neural Information Processing Systems (NeurIPS), 2019 | 37 | 2019 |
| Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data S Frei, G Vardi, PL Bartlett, N Srebro, W Hu International Conference on Learning Representations (ICLR), 2023 | 36 | 2023 |
| Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent S Frei, Q Gu Advances in Neural Information Processing Systems (NeurIPS), 2021 | 28 | 2021 |
| Random Feature Amplification: Feature Learning and Generalization in Neural Networks S Frei, NS Chatterji, PL Bartlett Journal of Machine Learning Research 24 (303), 2023 | 27 | 2023 |
| Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization S Frei, G Vardi, PL Bartlett, N Srebro Conference on Learning Theory (COLT), 2023 | 24 | 2023 |
| Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise S Frei, Y Cao, Q Gu International Conference on Machine Learning (ICML), 2021 | 20 | 2021 |
| Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins S Frei, Y Cao, Q Gu International Conference on Machine Learning (ICML), 2021 | 19 | 2021 |
| Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data Z Xu, Y Wang, S Frei, G Vardi, W Hu International Conference on Learning Representations (ICLR), 2024 | 18 | 2024 |
| Self-training converts weak learners to strong learners in mixture models S Frei, D Zou, Z Chen, Q Gu International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 | 18 | 2022 |
| Provable Robustness of Adversarial Training for Learning Halfspaces with Noise D Zou, S Frei, Q Gu International Conference on Machine Learning (ICML), 2021 | 14 | 2021 |
| The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks S Frei, G Vardi, PL Bartlett, N Srebro Advances in Neural Information Processing Systems (NeurIPS), 2023 | 13 | 2023 |
| A lower bound for in range- bond percolation in two and three dimensions S Frei, E Perkins Electronic Journal of Probability 21, 2016 | 11 | 2016 |
| Hemodynamic latency is associated with reduced intelligence across the lifespan: an fMRI DCM study of aging, cerebrovascular integrity, and cognitive ability. AE Anderson, M Diaz‑Santos, S Frei, BH Dang, P Kaur, P Lyden, ... Brain Structure & Function, 2020 | 9 | 2020 |
| On thermal resistance in concentric residential geothermal heat exchangers S Frei, K Lockwood, G Stewart, J Boyer, BS Tilley Journal of Engineering Mathematics 86 (1), 103-124, 2014 | 4 | 2014 |
| Minimum-Norm Interpolation Under Covariate Shift N Mallinar, A Zane, S Frei, B Yu arXiv preprint arXiv:2404.00522, 2024 | | 2024 |
| The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning N Ghosh, S Frei, W Ha, B Yu arXiv preprint arXiv:2308.03215, 2023 | | 2023 |
Peter BartlettProfessor, EECS and Statistics, UC Berkeley在 cs.berkeley.edu 的电子邮件经过验证
