| Making the last iterate of sgd information theoretically optimal P Jain, D Nagaraj, P Netrapalli Conference on Learning Theory, 1752-1755, 2019 | 65 | 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 | 59* | 2019 |
| A law of robustness for two-layers neural networks S Bubeck, Y Li, DM Nagaraj Conference on Learning Theory, 804-820, 2021 | 37 | 2021 |
| 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 | 30 | 2020 |
| Optimal Single Sample Tests for Structured versus Unstructured Network Data G Bresler, D Nagaraj arXiv preprint arXiv:1802.06186, 2018 | 25 | 2018 |
| Stein’s method for stationary distributions of Markov chains and application to Ising models G Bresler, D Nagaraj | 22 | 2019 |
| Phase transitions for detecting latent geometry in random graphs M Brennan, G Bresler, D Nagaraj Probability Theory and Related Fields 178 (3-4), 1215-1289, 2020 | 20 | 2020 |
| 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 | 19 | 2021 |
| Continuous limit of discrete quantum walks MN Dheeraj, TA Brun Physical Review A 91 (6), 062304, 2015 | 19 | 2015 |
| 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 | 16 | 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 | 15 | 2021 |
| 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 | 14 | 2021 |
| A corrective view of neural networks: Representation, memorization and learning G Bresler, D Nagaraj Conference on Learning Theory, 848-901, 2020 | 14 | 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 | 12* | 2021 |
| Open Problem: Do Good Algorithms Necessarily Query Bad Points? R Ge, P Jain, SM Kakade, R Kidambi, DM Nagaraj, P Netrapalli Conference on Learning Theory, 3190-3193, 2019 | 3 | 2019 |
| Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularization D Nagaraj, D Precup, G Patil, LA Prashanth | | 2023 |
| 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 | | 2022 |
| Multi-User Reinforcement Learning with Low Rank Rewards N Agarwal, P Jain, S Kowshik, D Nagaraj, P Netrapalli arXiv preprint arXiv:2210.05355, 2022 | | 2022 |
| Metastable Mixing of Markov Chains: Efficiently Sampling Low Temperature Exponential Random Graphs G Bresler, D Nagaraj, E Nichani arXiv preprint arXiv:2208.13153, 2022 | | 2022 |
| Look Back When Surprised: Stabilizing Reverse Experience Replay for Neural Approximation R Kumar, D Nagaraj arXiv preprint arXiv:2206.03171, 2022 | | 2022 |
Praneeth NetrapalliGoogle ResearchPotvrđena adresa e-pošte na google.com
