| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 3326 | 2021 |
| Holistic evaluation of language models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022 | 769 | 2022 |
| Underdamped Langevin MCMC: A non-asymptotic analysis X Cheng, NS Chatterji, PL Bartlett, MI Jordan Conference on Learning Theory 75, 300--323, 2018 | 324 | 2018 |
| Convergence rates for Langevin Monte Carlo in the nonconvex setting X Cheng, NS Chatterji, Y Abbasi-Yadkori, PL Bartlett, MI Jordan arXiv preprint arXiv:1805.01648, 2018 | 183* | 2018 |
| Is there an analog of Nesterov acceleration for gradient-based MCMC? YA Ma, NS Chatterji, X Cheng, N Flammarion, PL Bartlett, MI Jordan Bernoulli 27 (3), 1942--1992, 2021 | 156 | 2021 |
| Finite-sample analysis of interpolating linear classifiers in the overparameterized regime NS Chatterji, PM Long Journal of Machine Learning Reseach 22 (129), 1--30, 2021 | 123 | 2021 |
| On the theory of variance reduction for stochastic gradient Monte Carlo NS Chatterji, N Flammarion, YA Ma, PL Bartlett, MI Jordan International Conference on Machine Learning 80, 764--773, 2018 | 96 | 2018 |
| 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 178, 2668--2703, 2022 | 74 | 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 |
| On the opportunities and risks of foundation models (arXiv: 2108.07258). arXiv R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... | 55 | 2022 |
| Proving test set contamination in black box language models Y Oren, N Meister, N Chatterji, F Ladhak, TB Hashimoto arXiv preprint arXiv:2310.17623, 2023 | 46 | 2023 |
| Langevin Monte Carlo without smoothness NS Chatterji, J Diakonikolas, MI Jordan, PL Bartlett International Conference on Artificial Intelligence and Statistics 108, 1716 …, 2020 | 44 | 2020 |
| OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits NS Chatterji, V Muthukumar, PL Bartlett International Conference on Artificial Intelligence and Statistics 108, 1844 …, 2020 | 43 | 2020 |
| Alternating minimization for dictionary learning with random initialization NS Chatterji, PL Bartlett Advances in Neural Information Processing Systems 30, 2017 | 42* | 2017 |
| Enhancement of spin-transfer torque switching via resonant tunneling NS Chatterji, AA Tulapurkar, B Muralidharan Applied Physics Letters 105 (23), 232410, 2014 | 30 | 2014 |
| Random feature amplification: Feature learning and generalization in neural networks S Frei, NS Chatterji, PL Bartlett arXiv preprint arXiv:2202.07626, 2022 | 27 | 2022 |
| On the theory of reinforcement learning with once-per-episode feedback NS Chatterji, A Pacchiano, PL Bartlett, MI Jordan Advances in Neural Information Processing Systems 34, 3401--3412, 2021 | 27 | 2021 |
| Online learning with kernel losses NS Chatterji, A Pacchiano, PL Bartlett International Conference on Machine Learning 97, 971--980, 2019 | 25* | 2019 |
| Is importance weighting incompatible with interpolating classifiers? KA Wang, NS Chatterji, S Haque, T Hashimoto International Conference on Learning Representations, 2022 | 23 | 2022 |
| The interplay between implicit bias and benign overfitting in two-layer linear networks NS Chatterji, PM Long, PL Bartlett Journal of Machine Learning Research 23 (263), 1--48, 2021 | 23 | 2021 |
Peter BartlettProfessor, EECS and Statistics, UC Berkeley在 cs.berkeley.edu 的电子邮件经过验证
