Shubhada Agrawal

According to our database, Shubhada Agrawal authored at least 17 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise.

Shubhada Agrawal, Siva Theja Maguluri, Martin Zubeldia

CoRR, May, 2026

Cover meets Robbins while Betting on Bounded Data: ln n Regret and Almost Sure ln ln n Regret.

Shubhada Agrawal, Aaditya Ramdas

CoRR, April, 2026

Regret Tail Characterization of Optimal Bandit Algorithms with Generic Rewards.

Subhodip Panda, Shubhada Agrawal

CoRR, April, 2026

Dual Representation of Minimum Divergence Under Integral Constraints.

Shubhanshu Shekhar, Shubhada Agrawal

CoRR, March, 2026

Asymptotically Optimal Sequential Testing with Markovian Data.

Alhad Sethi, Kavali Sofia Sagar, Shubhada Agrawal, Debabrota Basu, P. N. Karthik

CoRR, February, 2026

2025

Eventually LIL Regret: Almost Sure ln ln T Regret for a sub-Gaussian Mixture on Unbounded Data.

Shubhada Agrawal, Aaditya Ramdas

CoRR, December, 2025

On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds.

Shubhada Agrawal, Aaditya Ramdas

CoRR, April, 2025

2024

Optimal Top-Two Method for Best Arm Identification and Fluid Analysis.

Agniv Bandyopadhyay, Sandeep Juneja, Shubhada Agrawal

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Policy Evaluation for Variance in Average Reward Reinforcement Learning.

Shubhada Agrawal, Prashanth L. A., Siva Theja Maguluri

Proceedings of the Forty-first International Conference on Machine Learning, 2024

CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption.

Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Shift, scale and restart smaller models to estimate larger ones: Agent based simulators in epidemiology.

Daksh Mittal, Sandeep Juneja, Shubhada Agrawal

SIGMETRICS Perform. Evaluation Rev., April, 2023

Optimal Best-Arm Identification in Bandits with Access to Offline Data.

Shubhada Agrawal, Sandeep Juneja, Karthikeyan Shanmugam, Arun Sai Suggala

CoRR, 2023

2021

Optimal Best-Arm Identification Methods for Tail-Risk Measures.

Shubhada Agrawal, Wouter M. Koolen, Sandeep Juneja

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Regret Minimization in Heavy-Tailed Bandits.

Shubhada Agrawal, Sandeep Juneja, Wouter M. Koolen

Proceedings of the Conference on Learning Theory, 2021

2020

City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic.

Shubhada Agrawal, Siddharth Bhandari, Anirban Bhattacharjee, Anand Deo, Narendra M. Dixit, Prahladh Harsha, Sandeep Juneja, Poonam Kesarwani, Aditya Krishna Swamy, Preetam Patil, Nihesh Rathod, Ramprasad Saptharishi, Sharad Shriram, Piyush Srivastava, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan, Sarath Yasodharan

CoRR, 2020

Optimal $δ$-Correct Best-Arm Selection for Heavy-Tailed Distributions.

Shubhada Agrawal, Sandeep Juneja, Peter W. Glynn

Proceedings of the Algorithmic Learning Theory, 2020

2019

Optimal best arm selection for general distributions.

Shubhada Agrawal, Sandeep Juneja, Peter W. Glynn

CoRR, 2019