Dheeraj Nagaraj

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 37

Top Topics

Convex Functions

Temporal Difference

Stochastic Approximation

Diffusion Models

Top Venues

Publications

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 (2024)
Harshit Varma, Dheeraj Nagaraj, Karthikeyan Shanmugam
Glauber Generative Model: Discrete Diffusion Models via Binary Classification. CoRR (2024)
Saravanan Kandasamy, Dheeraj Nagaraj
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models. CoRR (2024)
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)
Ramnath Kumar, Kushal Majmundar, Dheeraj Nagaraj, Arun Sai Suggala
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization. CoRR (2023)
Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. AAMAS (2023)
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)
Aniket Das, Dheeraj Nagaraj
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation. CoRR (2023)
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 (2023)
Dheeraj Baby, Aniket Das, Dheeraj Nagaraj, Praneeth Netrapalli
Near Optimal Heteroscedastic Regression with Symbiotic Learning. CoRR (2023)
Aniket Das, Dheeraj Nagaraj
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation. NeurIPS (2023)
Ramnath Kumar, Dheeraj Nagaraj
Look Back When Surprised: Stabilizing Reverse Experience Replay for Neural Approximation. CoRR (2022)
Dheeraj Nagaraj
Entropic Convergence of Random Batch Methods for Interacting Particle Diffusion. CoRR (2022)
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 (2022)
Abheek Ghosh, Dheeraj Nagaraj, Manish Jain, Milind Tambe
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits. CoRR (2022)
Naman Agarwal, Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
Multi-User Reinforcement Learning with Low Rank Rewards. CoRR (2022)
Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
Streaming Linear System Identification with Reverse Experience Replay. CoRR (2021)
Suhas S. Kowshik, Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. NeurIPS (2021)
Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj
The staircase property: How hierarchical structure can guide deep learning. NeurIPS (2021)
Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
Streaming Linear System Identification with Reverse Experience Replay. NeurIPS (2021)
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 (2021)
Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. CoRR (2021)
Emmanuel Abbe, Enric Boix-Adserà, Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj
The staircase property: How hierarchical structure can guide deep learning. CoRR (2021)
Guy Bresler, Dheeraj Nagaraj
A Corrective View of Neural Networks: Representation, Memorization and Learning. COLT (2020)
Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain, Praneeth Netrapalli
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. NeurIPS (2020)
Guy Bresler, Dheeraj Nagaraj
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. CoRR (2020)
Sébastien Bubeck, Yuanzhi Li, Dheeraj Nagaraj
A law of robustness for two-layers neural networks. CoRR (2020)
Guy Bresler, Dheeraj Nagaraj
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth. NeurIPS (2020)
Guy Bresler, Dheeraj Nagaraj
A Corrective View of Neural Networks: Representation, Memorization and Learning. CoRR (2020)
Guy Bresler, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli, Xian Wu
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. CoRR (2020)
Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
Making the Last Iterate of SGD Information Theoretically Optimal. CoRR (2019)
Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
SGD without Replacement: Sharper Rates for General Smooth Convex Functions. CoRR (2019)
Matthew S. Brennan, Guy Bresler, Dheeraj Nagaraj
Phase Transitions for Detecting Latent Geometry in Random Graphs. CoRR (2019)
Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli
SGD without Replacement: Sharper Rates for General Smooth Convex Functions. ICML (2019)
Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
Making the Last Iterate of SGD Information Theoretically Optimal. COLT (2019)
Guy Bresler, Dheeraj Nagaraj
Optimal Single Sample Tests for Structured versus Unstructured Network Data. COLT (2018)
Guy Bresler, Dheeraj Nagaraj
Optimal Single Sample Tests for Structured versus Unstructured Network Data. CoRR (2018)