| 2025 | ACL | Compute Optimal Scaling of Skills: Knowledge vs Reasoning. | Nicholas Roberts, Niladri S. Chatterji, Sharan Narang, Mike Lewis, Dieuwke Hupkes |
| 2024 | ICLR | Proving Test Set Contamination in Black-Box Language Models. | Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, Tatsunori Hashimoto |
| 2022 | COLT | Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. | Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett |
| 2021 | COLT | When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations? | Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett |
| 2020 | AISTATS | Langevin Monte Carlo without smoothness. | Niladri S. Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter L. Bartlett |
| 2020 | AISTATS | OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits. | Niladri S. Chatterji, Vidya Muthukumar, Peter L. Bartlett |
| 2020 | ICLR | The intriguing role of module criticality in the generalization of deep networks. | Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi |
| 2019 | ICML | Online learning with kernel losses. | Niladri S. Chatterji, Aldo Pacchiano, Peter L. Bartlett |
| 2018 | COLT | Underdamped Langevin MCMC: A non-asymptotic analysis. | Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett, Michael I. Jordan |
| 2018 | ICML | On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo. | Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma, Peter L. Bartlett, Michael I. Jordan |