Optimal Single Sample Tests for Structured versus Unstructured Network Data. - Guy Bresler; Dheeraj Nagaraj (COLT, 2018)

Open Problem: Do Good Algorithms Necessarily Query Bad Points? - Rong Ge 001; Prateek Jain 002; Sham M. Kakade; Rahul Kidambi; Dheeraj M. Nagaraj; Praneeth Netrapalli (COLT, 2019)

SGD without Replacement: Sharper Rates for General Smooth Convex Functions. - Dheeraj Nagaraj; Prateek Jain 002; Praneeth Netrapalli (ICML, 2019)

Phase Transitions for Detecting Latent Geometry in Random Graphs. - Matthew S. Brennan; Guy Bresler; Dheeraj Nagaraj (CoRR, 2019)

A Corrective View of Neural Networks: Representation, Memorization and Learning. - Guy Bresler; Dheeraj Nagaraj (COLT, 2020)

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. - Guy Bresler; Dheeraj Nagaraj (NeurIPS, 2020)

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. - Dheeraj Nagaraj; Xian Wu 009; Guy Bresler; Prateek Jain 002; Praneeth Netrapalli (NeurIPS, 2020)

A Law of Robustness for Two-Layers Neural Networks. - Sébastien Bubeck; Yuanzhi Li; Dheeraj M. Nagaraj (COLT, 2021)

The staircase property: How hierarchical structure can guide deep learning. - Emmanuel Abbe; Enric Boix-Adserà; Matthew S. Brennan; Guy Bresler; Dheeraj Nagaraj (NeurIPS, 2021)

Streaming Linear System Identification with Reverse Experience Replay. - Prateek Jain 002; Suhas S. Kowshik; Dheeraj Nagaraj; Praneeth Netrapalli (NeurIPS, 2021)

Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. - Suhas S. Kowshik; Dheeraj Nagaraj; Prateek Jain 002; Praneeth Netrapalli (NeurIPS, 2021)

Making the Last Iterate of SGD Information Theoretically Optimal. - Prateek Jain 002; Dheeraj M. Nagaraj; Praneeth Netrapalli (SIAM J. Optim., 2021)

Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. - Naman Agarwal; Syomantak Chaudhuri; Prateek Jain 002; Dheeraj Mysore Nagaraj; Praneeth Netrapalli (ICLR, 2022)

Look Back When Surprised: Stabilizing Reverse Experience Replay for Neural Approximation. - Ramnath Kumar; Dheeraj Nagaraj (CoRR, 2022)

Entropic Convergence of Random Batch Methods for Interacting Particle Diffusion. - Dheeraj Nagaraj (CoRR, 2022)

Expressivity and Structure in Networks: Ising Models, Random Graphs, and Neural Networks. - Dheeraj M. Nagaraj (2022)

Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation. - Gandharv Patil; Prashanth L. A.; Dheeraj Nagaraj; Doina Precup (AISTATS, 2023)

Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. - Abheek Ghosh; Dheeraj Nagaraj; Manish Jain; Milind Tambe (AAMAS, 2023)

Near Optimal Heteroscedastic Regression with Symbiotic Learning. - Aniket Das; Dheeraj M. Nagaraj; Praneeth Netrapalli; Dheeraj Baby (COLT, 2023)

Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms. - Aniket Das; Dheeraj M. Nagaraj; Anant Raj (COLT, 2023)

Multi-User Reinforcement Learning with Low Rank Rewards. - Dheeraj Mysore Nagaraj; Suhas S. Kowshik; Naman Agarwal; Praneeth Netrapalli; Prateek Jain 002 (ICML, 2023)

Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation. - Aniket Das; Dheeraj Nagaraj (NeurIPS, 2023)

Towards Zero Shot Learning in Restless Multi-armed Bandits. - Yunfan Zhao; Nikhil Behari; Edward Hughes 001; Edwin Zhang; Dheeraj Nagaraj; Karl Tuyls; Aparna Taneja; Milind Tambe (AAMAS, 2024)

Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization. - Yunfan Zhao; Nikhil Behari; Edward Hughes 001; Edwin Zhang; Dheeraj Nagaraj; Karl Tuyls; Aparna Taneja; Milind Tambe (IJCAI, 2024)

The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models. - Saravanan Kandasamy 002; Dheeraj Nagaraj (NeurIPS, 2024)

A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health. - Nikhil Behari; Edwin Zhang; Yunfan Zhao; Aparna Taneja; Dheeraj Nagaraj; Milind Tambe (NeurIPS, 2024)

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD. - Aniket Das; Dheeraj Nagaraj; Soumyabrata Pal; Arun Sai Suggala; Prateek Varshney (NeurIPS, 2024)

Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization. - Ramnath Kumar; Kushal Majmundar; Dheeraj Mysore Nagaraj; Arun Sai Suggala (Trans. Mach. Learn. Res., 2024)

Introspective Experience Replay: Look Back When Surprised. - Ramnath Kumar; Dheeraj Mysore Nagaraj (Trans. Mach. Learn. Res., 2024)

The Bandit Whisperer: Communication Learning for Restless Bandits. - Yunfan Zhao; Tonghan Wang 001; Dheeraj Mysore Nagaraj; Aparna Taneja; Milind Tambe (AAAI, 2025)

Beyond propagation of chaos: A stochastic algorithm for mean field optimization. - Chandan Tankala; Dheeraj Nagaraj; Anant Raj (COLT, 2025)

Glauber Generative Model: Discrete Diffusion Models via Binary Classification. - Harshit Varma; Dheeraj Mysore Nagaraj; Karthikeyan Shanmugam (ICLR, 2025)

Dimension-free Score Matching and Time Bootstrapping for Diffusion Models. - Syamantak Kumar; Dheeraj Nagaraj; Purnamrita Sarkar (CoRR, 2025)

Interleaved Gibbs Diffusion for Constrained Generation. - Gautham Govind Anil; Sachin Yadav; Dheeraj Nagaraj; Karthikeyan Shanmugam; Prateek Jain 002 (CoRR, 2025)

Poisson Midpoint Method for Log Concave Sampling: Beyond the Strong Error Lower Bounds. - Rishikesh Srinivasan; Dheeraj Nagaraj (CoRR, 2025)