See also my Google Scholar profile.

AISTATS
Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits
Ramakrishnan K, Arpit Agarwal, Lakshmi Subramanian, Maximilian Nickel
International Conference on Artificial Intelligence and Statistics, 2026
Oral Presentation (top 10 / ~2100)
ICLR
Ads that Stick: Near-Optimal Ad Optimization through Psychological Behavior Models
Kailash Gopal Darmasubramanian, Akash Pareek, Arindam Khan, Arpit Agarwal
International Conference on Learning Representations, 2026
WINE
Misalignment, Learning, and Ranking: Harnessing Users Limited Attention
Arpit Agarwal, Rad Niazadeh, Prathamesh Patil (alphabetical)
Web and Internet Economics, 2025
TMLR
Non-Stationary Dueling Bandits Under a Weighted Borda Criterion
Joe Suk, Arpit Agarwal
Transactions on Machine Learning Research, 2025
Invited for presentation at ICLR 2025
NeurIPS
Learning-Augmented Dynamic Submodular Maximization
Arpit Agarwal, Eric Balkanski
Neural Information Processing Systems, 2024
FOCS
Semi-Bandit Learning for Monotone Stochastic Optimization
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan (alphabetical)
IEEE Symposium on Foundations of Computer Science, 2024
FAccT
System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes
Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel
ACM Conference on Fairness, Accountability, and Transparency, 2024
ALT
Online Recommendations for Agents with Discounted Adaptive Preferences
Arpit Agarwal, William Brown (alphabetical)
International Conference on Algorithmic Learning Theory, 2024
SODA
Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth
Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil, Chen Wang, Nathan White, Peilin Zhong (alphabetical)
ACM-SIAM Symposium on Discrete Algorithms, 2024
NeurIPS
When Can We Track Significant Preference Shifts in Dueling Bandits?
Joe Suk, Arpit Agarwal
Neural Information Processing Systems, 2023
NeurIPS
Diversified Recommendations for Agents with Adaptive Preferences
Arpit Agarwal, William Brown (alphabetical)
Neural Information Processing Systems, 2022
NeurIPS
Sublinear Algorithms for Hierarchical Clustering
Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil (alphabetical)
Neural Information Processing Systems, 2022
NeurIPS
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan (alphabetical)
Neural Information Processing Systems, 2022
COLT
A Sharp Memory-Regret Trade-Off for Multi-Pass Streaming Bandits
Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil (alphabetical)
Conference on Learning Theory, 2022
ICML
Batched Dueling Bandits
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan (alphabetical)
International Conference on Machine Learning, 2022
Long presentation (top 2%)
AISTATS
PAC Top-k Identification under SST in Limited Rounds
Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil (alphabetical)
International Conference on Artificial Intelligence and Statistics, 2022
ALT
Stochastic Dueling Bandits with Adversarial Corruption
Arpit Agarwal, Shivani Agarwal, Prathamesh Patil (alphabetical)
International Conference on Algorithmic Learning Theory, 2021
NeurIPS
Choice Bandits
Arpit Agarwal, Nicholas Johnson, Shivani Agarwal
Neural Information Processing Systems, 2020
ICML
Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions
Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil (alphabetical)
International Conference on Machine Learning, 2020
ACM TEAC
Peer Prediction with Heterogeneous Users
Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah (alphabetical)
ACM Transactions on Economics and Computation, 2020
SODA
Stochastic Submodular Cover with Limited Adaptivity
Arpit Agarwal, Sepehr Assadi, Sanjeev Khanna (alphabetical)
ACM-SIAM Symposium on Discrete Algorithms, 2019
ICML
Accelerated Spectral Ranking
Arpit Agarwal, Prathamesh Patil, Shivani Agarwal
International Conference on Machine Learning, 2018
COLT
Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons
Arpit Agarwal, Shivani Agarwal, Sepehr Assadi, Sanjeev Khanna (alphabetical)
Conference on Learning Theory, 2017
EC
Peer Prediction with Heterogeneous Users
Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah (alphabetical)
ACM Conference on Economics and Computation, 2017
EC
Informed Truthfulness in Multi-Task Peer Prediction
Victor Shnayder, Arpit Agarwal, Rafael Frongillo, David C. Parkes
ACM Conference on Economics and Computation, 2016
COLT
On Consistent Surrogate Risk Minimization and Property Elicitation
Arpit Agarwal, Shivani Agarwal
Conference on Learning Theory, 2015
ICML
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare
International Conference on Machine Learning, 2014