| 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 | 4360 | 2021 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 1222 | 2024 |
| 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 | 1086 | 2022 |
| Underdamped Langevin MCMC: A non-asymptotic analysis X Cheng, NS Chatterji, PL Bartlett, MI Jordan Conference on Learning Theory 75, 300--323, 2018 | 347 | 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 | 188* | 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 | 171 | 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 | 140 | 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 | 103 | 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 | 94 | 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 | 87 | 2023 |
| 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, ... | 78 | 2022 |
| & Liang, P.(2021). 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, 0 | 72 | |
| The intriguing role of module criticality in the generalization of deep networks NS Chatterji, B Neyshabur, H Sedghi International Conference on Learning Representations, 2020 | 65 | 2020 |
| On the opportunities and risks of foundation models (2021) R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2022 | 63 | 2022 |
| Langevin Monte Carlo without smoothness NS Chatterji, J Diakonikolas, MI Jordan, PL Bartlett International Conference on Artificial Intelligence and Statistics 108, 1716 …, 2020 | 50 | 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 | 45 | 2020 |
| Alternating minimization for dictionary learning with random initialization NS Chatterji, PL Bartlett Advances in Neural Information Processing Systems 30, 2017 | 43* | 2017 |
| Random feature amplification: Feature learning and generalization in neural networks S Frei, NS Chatterji, PL Bartlett arXiv preprint arXiv:2202.07626, 2022 | 32 | 2022 |
| Enhancement of spin-transfer torque switching via resonant tunneling NS Chatterji, AA Tulapurkar, B Muralidharan Applied Physics Letters 105 (23), 232410, 2014 | 31 | 2014 |
| 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 | 28 | 2021 |
Peter BartlettProfessor, EECS and Statistics, UC Berkeleyכתובת אימייל מאומתת בדומיין cs.berkeley.edu
