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Dheeraj Nagaraj
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2020 – today
- 2024
- [j2]Ramnath Kumar, Dheeraj Mysore Nagaraj:
Introspective Experience Replay: Look Back When Surprised. Trans. Mach. Learn. Res. 2024 (2024) - [c20]Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe:
Towards Zero Shot Learning in Restless Multi-armed Bandits. AAMAS 2024: 2618-2620 - [c19]Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe:
Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization. IJCAI 2024: 321-329 - [i25]Nikhil Behari, Edwin Zhang, Yunfan Zhao, Aparna Taneja, Dheeraj Nagaraj, Milind Tambe:
A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health. CoRR abs/2402.14807 (2024) - [i24]Harshit Varma, Dheeraj Nagaraj, Karthikeyan Shanmugam:
Glauber Generative Model: Discrete Diffusion Models via Binary Classification. CoRR abs/2405.17035 (2024) - [i23]Saravanan Kandasamy, Dheeraj Nagaraj:
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models. CoRR abs/2405.17068 (2024) - [i22]Yunfan Zhao, Tonghan Wang, Dheeraj Nagaraj, Aparna Taneja, Milind Tambe:
The Bandit Whisperer: Communication Learning for Restless Bandits. CoRR abs/2408.05686 (2024) - 2023
- [c18]Gandharv Patil, Prashanth L. A., Dheeraj Nagaraj, Doina Precup:
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation. AISTATS 2023: 5438-5448 - [c17]Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe:
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. AAMAS 2023: 1294-1302 - [c16]Aniket Das, Dheeraj M. Nagaraj, Praneeth Netrapalli, Dheeraj Baby:
Near Optimal Heteroscedastic Regression with Symbiotic Learning. COLT 2023: 3696-3757 - [c15]Aniket Das, Dheeraj M. Nagaraj, Anant Raj:
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms. COLT 2023: 4072-4129 - [c14]Dheeraj Mysore Nagaraj, Suhas S. Kowshik, Naman Agarwal, Praneeth Netrapalli, Prateek Jain:
Multi-User Reinforcement Learning with Low Rank Rewards. ICML 2023: 25627-25659 - [c13]Aniket Das, Dheeraj Nagaraj:
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation. NeurIPS 2023 - [i21]Aniket Das, Dheeraj Nagaraj:
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation. CoRR abs/2305.17558 (2023) - [i20]Ramnath Kumar, Kushal Majmundar, Dheeraj Nagaraj, Arun Sai Suggala:
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization. CoRR abs/2306.09222 (2023) - [i19]Dheeraj Baby, Aniket Das, Dheeraj Nagaraj, Praneeth Netrapalli:
Near Optimal Heteroscedastic Regression with Symbiotic Learning. CoRR abs/2306.14288 (2023) - [i18]Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe:
Towards Zero Shot Learning in Restless Multi-armed Bandits. CoRR abs/2310.14526 (2023) - 2022
- [b1]Dheeraj M. Nagaraj:
Expressivity and Structure in Networks: Ising Models, Random Graphs, and Neural Networks. Massachusetts Institute of Technology, USA, 2022 - [c12]Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli:
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. ICLR 2022 - [i17]Ramnath Kumar, Dheeraj Nagaraj:
Look Back When Surprised: Stabilizing Reverse Experience Replay for Neural Approximation. CoRR abs/2206.03171 (2022) - [i16]Dheeraj Nagaraj:
Entropic Convergence of Random Batch Methods for Interacting Particle Diffusion. CoRR abs/2206.03792 (2022) - [i15]Naman Agarwal, Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli:
Multi-User Reinforcement Learning with Low Rank Rewards. CoRR abs/2210.05355 (2022) - [i14]Gandharv Patil, Prashanth L. A., Dheeraj Nagaraj, Doina Precup:
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation. CoRR abs/2210.05918 (2022) - [i13]Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe:
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. CoRR abs/2211.00112 (2022) - 2021
- [j1]Prateek Jain, Dheeraj M. Nagaraj, Praneeth Netrapalli:
Making the Last Iterate of SGD Information Theoretically Optimal. SIAM J. Optim. 31(2): 1108-1130 (2021) - [c11]Sébastien Bubeck, Yuanzhi Li, Dheeraj M. Nagaraj:
A Law of Robustness for Two-Layers Neural Networks. COLT 2021: 804-820 - [c10]Suhas S. Kowshik, Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli:
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. NeurIPS 2021: 8518-8531 - [c9]Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
The staircase property: How hierarchical structure can guide deep learning. NeurIPS 2021: 26989-27002 - [c8]Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli:
Streaming Linear System Identification with Reverse Experience Replay. NeurIPS 2021: 30140-30152 - [i12]Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli:
Streaming Linear System Identification with Reverse Experience Replay. CoRR abs/2103.05896 (2021) - [i11]Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli:
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. CoRR abs/2105.11558 (2021) - [i10]Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
The staircase property: How hierarchical structure can guide deep learning. CoRR abs/2108.10573 (2021) - [i9]Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli:
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. CoRR abs/2110.08440 (2021) - 2020
- [c7]Guy Bresler, Dheeraj Nagaraj:
A Corrective View of Neural Networks: Representation, Memorization and Learning. COLT 2020: 848-901 - [c6]Guy Bresler, Dheeraj Nagaraj:
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. NeurIPS 2020 - [c5]Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain, Praneeth Netrapalli:
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. NeurIPS 2020 - [i8]Guy Bresler, Dheeraj Nagaraj:
A Corrective View of Neural Networks: Representation, Memorization and Learning. CoRR abs/2002.00274 (2020) - [i7]Guy Bresler, Dheeraj Nagaraj:
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. CoRR abs/2006.04048 (2020) - [i6]Guy Bresler, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli, Xian Wu:
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. CoRR abs/2006.08916 (2020) - [i5]Sébastien Bubeck, Yuanzhi Li, Dheeraj Nagaraj:
A law of robustness for two-layers neural networks. CoRR abs/2009.14444 (2020)
2010 – 2019
- 2019
- [c4]Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli:
Making the Last Iterate of SGD Information Theoretically Optimal. COLT 2019: 1752-1755 - [c3]Rong Ge, Prateek Jain, Sham M. Kakade, Rahul Kidambi, Dheeraj M. Nagaraj, Praneeth Netrapalli:
Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT 2019: 3190-3193 - [c2]Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli:
SGD without Replacement: Sharper Rates for General Smooth Convex Functions. ICML 2019: 4703-4711 - [i4]Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli:
SGD without Replacement: Sharper Rates for General Smooth Convex Functions. CoRR abs/1903.01463 (2019) - [i3]Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli:
Making the Last Iterate of SGD Information Theoretically Optimal. CoRR abs/1904.12443 (2019) - [i2]Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj:
Phase Transitions for Detecting Latent Geometry in Random Graphs. CoRR abs/1910.14167 (2019) - 2018
- [c1]Guy Bresler, Dheeraj Nagaraj:
Optimal Single Sample Tests for Structured versus Unstructured Network Data. COLT 2018: 1657-1690 - [i1]Guy Bresler, Dheeraj Nagaraj:
Optimal Single Sample Tests for Structured versus Unstructured Network Data. CoRR abs/1802.06186 (2018)
Coauthor Index
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