| Making the last iterate of sgd information theoretically optimal P Jain, D Nagaraj, P Netrapalli Conference on Learning Theory, 1752-1755, 2019 | 107 | 2019 |
| SGD without Replacement: Sharper Rates for General Smooth Convex Functions D Nagaraj, P Jain, P Netrapalli International Conference on Machine Learning, 4703-4711, 2019 | 94* | 2019 |
| Least squares regression with markovian data: Fundamental limits and algorithms D Nagaraj, X Wu, G Bresler, P Jain, P Netrapalli Advances in neural information processing systems 33, 16666-16676, 2020 | 73 | 2020 |
| The staircase property: How hierarchical structure can guide deep learning E Abbe, E Boix-Adsera, MS Brennan, G Bresler, D Nagaraj Advances in Neural Information Processing Systems 34, 26989-27002, 2021 | 64 | 2021 |
| A law of robustness for two-layers neural networks S Bubeck, Y Li, DM Nagaraj Conference on Learning Theory, 804-820, 2021 | 60 | 2021 |
| Phase transitions for detecting latent geometry in random graphs M Brennan, G Bresler, D Nagaraj Probability Theory and Related Fields 178 (3), 1215-1289, 2020 | 42 | 2020 |
| Near-optimal offline and streaming algorithms for learning non-linear dynamical systems S Kowshik, D Nagaraj, P Jain, P Netrapalli Advances in Neural Information Processing Systems 34, 8518-8531, 2021 | 33 | 2021 |
| Stein’s method for stationary distributions of Markov chains and application to Ising models G Bresler, D Nagaraj | 30 | 2019 |
| Optimal Single Sample Tests for Structured versus Unstructured Network Data G Bresler, D Nagaraj arXiv preprint arXiv:1802.06186, 2018 | 30 | 2018 |
| Online target q-learning with reverse experience replay: Efficiently finding the optimal policy for linear mdps N Agarwal, S Chaudhuri, P Jain, D Nagaraj, P Netrapalli arXiv preprint arXiv:2110.08440, 2021 | 29 | 2021 |
| Sharp representation theorems for relu networks with precise dependence on depth G Bresler, D Nagaraj Advances in Neural Information Processing Systems 33, 10697-10706, 2020 | 27 | 2020 |
| Streaming linear system identification with reverse experience replay S Kowshik, D Nagaraj, P Jain, P Netrapalli Advances in Neural Information Processing Systems 34, 30140-30152, 2021 | 24 | 2021 |
| Continuous limit of discrete quantum walks D MN, TA Brun Physical Review A 91 (6), 062304, 2015 | 21 | 2015 |
| Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularization D Nagaraj, D Precup, G Patil, LA Prashanth | 18* | 2023 |
| A corrective view of neural networks: Representation, memorization and learning G Bresler, D Nagaraj Conference on Learning Theory, 848-901, 2020 | 18 | 2020 |
| Indexability is not enough for whittle: Improved, near-optimal algorithms for restless bandits A Ghosh, D Nagaraj, M Jain, M Tambe arXiv preprint arXiv:2211.00112, 2022 | 10 | 2022 |
| Stochastic re-weighted gradient descent via distributionally robust optimization R Kumar, K Majmundar, D Nagaraj, AS Suggala arXiv preprint arXiv:2306.09222, 2023 | 9 | 2023 |
| Provably fast finite particle variants of svgd via virtual particle stochastic approximation A Das, D Nagaraj Advances in Neural Information Processing Systems 36, 49748-49760, 2023 | 8 | 2023 |
| A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health N Behari, E Zhang, Y Zhao, A Taneja, D Nagaraj, M Tambe arXiv preprint arXiv:2402.14807, 2024 | 6 | 2024 |
| Towards a pretrained model for restless bandits via multi-arm generalization Y Zhao, N Behari, E Hughes, E Zhang, D Nagaraj, K Tuyls, A Taneja, ... Proc. of IJCAI, 321-329, 2024 | 6* | 2024 |
