Wireless scheduling with heterogeneously delayed network-state information. - Akula Aneesh Reddy; Siddhartha Banerjee; Aditya Gopalan; Sanjay Shakkottai; Lei Ying 001 (Allerton, 2010)

User rankings from comparisons: Learning permutations in high dimensions. - Ioannis Mitliagkas; Aditya Gopalan; Constantine Caramanis; Sriram Vishwanath (Allerton, 2011)

Random mobility and the spread of infection. - Aditya Gopalan; Siddhartha Banerjee; Abhik Kumar Das; Sanjay Shakkottai (INFOCOM, 2011)

Low-delay wireless scheduling with partial channel-state information. - Aditya Gopalan; Constantine Caramanis; Sanjay Shakkottai (INFOCOM, 2012)

On distributed scheduling with heterogeneously delayed network-state information. - Akula Aneesh Reddy; Siddhartha Banerjee; Aditya Gopalan; Sanjay Shakkottai; Lei Ying 001 (Queueing Syst. Theory Appl., 2012)

On Wireless Scheduling With Partial Channel-State Information. - Aditya Gopalan; Constantine Caramanis; Sanjay Shakkottai (IEEE Trans. Inf. Theory, 2012)

Thompson Sampling for Online Learning with Linear Experts. - Aditya Gopalan (CoRR, 2013)

Thompson Sampling for Complex Bandit Problems. - Aditya Gopalan; Shie Mannor; Yishay Mansour (CoRR, 2013)

On the Value of Coordination and Delayed Queue Information in Multicellular Scheduling. - Aditya Gopalan; Constantine Caramanis; Sanjay Shakkottai (IEEE Trans. Autom. Control., 2013)

Thompson Sampling for Complex Online Problems. - Aditya Gopalan; Shie Mannor; Yishay Mansour (ICML, 2014)

Thompson Sampling for Learning Parameterized MDPs. - Aditya Gopalan; Shie Mannor (CoRR, 2014)

Epidemic Spreading With External Agents. - Siddhartha Banerjee; Aditya Gopalan; Abhik Kumar Das; Sanjay Shakkottai (IEEE Trans. Inf. Theory, 2014)

A restless bandit with no observable states for recommendation systems and communication link scheduling. - Rahul Meshram; D. Manjunath; Aditya Gopalan (CDC, 2015)

Thompson Sampling for Learning Parameterized Markov Decision Processes. - Aditya Gopalan; Shie Mannor (COLT, 2015)

Optimal WiFi sensing via dynamic programming. - Abhinav Kumar; Sibi Raj B. Pillai; Rahul Vaze; Aditya Gopalan (WiOpt, 2015)

Wireless scheduling with partial channel state information: large deviations and optimality. - Aditya Gopalan; Constantine Caramanis; Sanjay Shakkottai (Queueing Syst. Theory Appl., 2015)

Randomised Procedures for Initialising and Switching Actions in Policy Iteration. - Shivaram Kalyanakrishnan; Neeldhara Misra; Aditya Gopalan (AAAI, 2016)

Optimal recommendation to users that react: Online learning for a class of POMDPs. - Rahul Meshram; Aditya Gopalan; D. Manjunath (CDC, 2016)

Optimizing distributed actor systems for dynamic interactive services. - Andrew Newell; Gabriel Kliot; Ishai Menache; Aditya Gopalan; Soramichi Akiyama; Mark Silberstein (EuroSys, 2016)

Low-rank Bandits with Latent Mixtures. - Aditya Gopalan; Odalric-Ambrym Maillard; Mohammadi Zaki (CoRR, 2016)

Stochastic bandits on a social network: Collaborative learning with local information sharing. - Ravi Kumar Kolla; Krishna P. Jagannathan; Aditya Gopalan (CoRR, 2016)

On the Whittle Index for Restless Multi-armed Hidden Markov Bandits. - Rahul Meshram; D. Manjunath; Aditya Gopalan (CoRR, 2016)

Misspecified Linear Bandits. - Avishek Ghosh; Sayak Ray Chowdhury; Aditya Gopalan (AAAI, 2017)

Weighted Bandits or: How Bandits Learn Distorted Values That Are Not Expected. - Aditya Gopalan; Prashanth L. A.; Michael C. Fu 001; Steven I. Marcus (AAAI, 2017)

Restless bandits that hide their hand and recommendation systems. - Rahul Meshram; Aditya Gopalan; D. Manjunath (COMSNETS, 2017)

A Hidden Markov Restless Multi-armed Bandit Model for Playout Recommendation Systems. - Rahul Meshram; Aditya Gopalan; D. Manjunath (COMSNETS (Revised Selected Papers and Invited Papers), 2017)

On Kernelized Multi-armed Bandits. - Sayak Ray Chowdhury; Aditya Gopalan (ICML, 2017)

When to arrive in a congested system: Achieving equilibrium via learning algorithm. - Parth Thaker; Aditya Gopalan; Rahul Vaze (WiOpt, 2017)

Optimal Odd Arm Identification with Fixed Confidence. - Gayathri R. Prabhu; Srikrishna Bhashyam; Aditya Gopalan; Rajesh Sundaresan (CoRR, 2017)

Online Learning for Structured Loss Spaces. - Siddharth Barman; Aditya Gopalan; Aadirupa Saha (AAAI, 2018)

Reduced-State, Optimal Medium Access Control for Wireless Data Collection Networks. - Avinash Mohan; Aditya Gopalan; Anurag Kumar 001 (INFOCOM, 2018)

On a Class of Restless Multi-armed Bandits with Deterministic Policies. - Prakirt Raj Jhunjhunwala; Sharayu Moharir; D. Manjunath; Aditya Gopalan (SPCOM, 2018)

Battle of Bandits. - Aadirupa Saha; Aditya Gopalan (UAI, 2018)

PAC-Battling Bandits with Plackett-Luce: Tradeoff between Sample Complexity and Subset Size. - Aditya Gopalan; Aadirupa Saha (CoRR, 2018)

On the Whittle Index for Restless Multiarmed Hidden Markov Bandits. - Rahul Meshram; D. Manjunath; Aditya Gopalan (IEEE Trans. Autom. Control., 2018)

Collaborative Learning of Stochastic Bandits Over a Social Network. - Ravi Kumar Kolla; Krishna P. Jagannathan; Aditya Gopalan (IEEE/ACM Trans. Netw., 2018)

Online Learning in Kernelized Markov Decision Processes. - Sayak Ray Chowdhury; Aditya Gopalan (AISTATS, 2019)

Active Ranking with Subset-wise Preferences. - Aadirupa Saha; Aditya Gopalan (AISTATS, 2019)

PAC Battling Bandits in the Plackett-Luce Model. - Aadirupa Saha; Aditya Gopalan (ALT, 2019)

Learning to Detect an Anomalous Target with Observations from an Exponential Family. - Gayathri R. Prabhu; Srikrishna Bhashyam; Aditya Gopalan; Rajesh Sundaresan (DSW, 2019)

Bayesian Optimization under Heavy-tailed Payoffs. - Sayak Ray Chowdhury; Aditya Gopalan (NeurIPS, 2019)

Combinatorial Bandits with Relative Feedback. - Aadirupa Saha; Aditya Gopalan (NeurIPS, 2019)

Regret Minimisation in Multinomial Logit Bandits. - Aadirupa Saha; Aditya Gopalan (CoRR, 2019)

On Batch Bayesian Optimization. - Sayak Ray Chowdhury; Aditya Gopalan (CoRR, 2019)

Towards Optimal and Efficient Best Arm Identification in Linear Bandits. - Mohammadi Zaki; Avinash Mohan; Aditya Gopalan (CoRR, 2019)

On Adaptivity in Information-Constrained Online Learning. - Siddharth Mitra; Aditya Gopalan (AAAI, 2020)

Sequential Mode Estimation with Oracle Queries. - Dhruti Shah; Tuhinangshu Choudhury; Nikhil Karamchandani; Aditya Gopalan (AAAI, 2020)

Best-item Learning in Random Utility Models with Subset Choices. - Aadirupa Saha; Aditya Gopalan (AISTATS, 2020)

CORNET: A Co-Simulation Middleware for Robot Networks. - Srikrishna Acharya; Bharadwaj S. Amrutur; Yogesh Simmhan; Aditya Gopalan; Parimal Parag; Himanshu Tyagi (COMSNETS, 2020)

From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model. - Aadirupa Saha; Aditya Gopalan (ICML, 2020)

On the Latency in Vehicular Control using Video Streaming over Wi-Fi. - Pratik Sharma; Devam Awasare; Bishal Jaiswal; Srivats Mohan; N. Abinaya; Ishan Darwhekar; Anand SVR; Bharadwaj Amrutur; Aditya Gopalan; Parimal Parag; Himanshu Tyagi (NCC, 2020)

Throughput Optimal Decentralized Scheduling with Single-bit State Feedback for a Class of Queueing Systems. - Avinash Mohan; Aditya Gopalan; Anurag Kumar 001 (CoRR, 2020)

How Reliable are Test Numbers for Revealing the COVID-19 Ground Truth and Applying Interventions? - Aditya Gopalan; Himanshu Tyagi (CoRR, 2020)

Explicit Best Arm Identification in Linear Bandits Using No-Regret Learners. - Mohammadi Zaki; Avinash Mohan; Aditya Gopalan (CoRR, 2020)

Stochastic Linear Bandits with Protected Subspace. - Advait Parulekar; Soumya Basu 001; Aditya Gopalan; Karthikeyan Shanmugam; Sanjay Shakkottai (CoRR, 2020)

Stability and Scalability of Blockchain Systems. - Aditya Gopalan; Abishek Sankararaman; Anwar Walid; Sriram Vishwanath (Proc. ACM Meas. Anal. Comput. Syst., 2020)

Reduced-State, Optimal Scheduling for Decentralized Medium Access Control of a Class of Wireless Networks. - Avinash Mohan; Aditya Gopalan; Anurag Kumar 001 (IEEE/ACM Trans. Netw., 2020)

No-regret Algorithms for Multi-task Bayesian Optimization. - Sayak Ray Chowdhury; Aditya Gopalan (AISTATS, 2021)

Reinforcement Learning in Parametric MDPs with Exponential Families. - Sayak Ray Chowdhury; Aditya Gopalan; Odalric-Ambrym Maillard (AISTATS, 2021)

Network Based Multi-Bot Awareness. - G. Dhanaprakaash; Bishal Jaiswal; Srikrishna Acharya; Anush Kumar; Aruul Mozhi Varman S; Kavish Shah; Mohitvishnu Srinivas Gadde; Sourav Mishra; Aditya Gopalan; Bharadwaj Amrutur; Himanshu Tyagi; Preetam Patil; et al. (COMSNETS, 2021)

Bandit Quickest Changepoint Detection. - Aditya Gopalan; Braghadeesh Lakshminarayanan; Venkatesh Saligrama (NeurIPS, 2021)

Improper Learning with Gradient-based Policy Optimization. - Mohammadi Zaki; Avinash Mohan; Aditya Gopalan; Shie Mannor (CoRR, 2021)

Better than the Best: Gradient-based Improper Reinforcement Learning for Network Scheduling. - Mohammadi Zaki; Avi Mohan; Aditya Gopalan; Shie Mannor (CoRR, 2021)

On Slowly-varying Non-stationary Bandits. - Ramakrishnan Krishnamurthy; Aditya Gopalan (CoRR, 2021)

Actor-Critic based Improper Reinforcement Learning. - Mohammadi Zaki; Avi Mohan; Aditya Gopalan; Shie Mannor (ICML, 2022)

Improved Pure Exploration in Linear Bandits with No-Regret Learning. - Mohammadi Zaki; Avi Mohan; Aditya Gopalan (IJCAI, 2022)

Adaptive Estimation of Random Vectors with Bandit Feedback. - Dipayan Sen; Prashanth L. A.; Aditya Gopalan (CoRR, 2022)

Approximate Q-learning and SARSA(0) under the ε-greedy Policy: a Differential Inclusion Analysis. - Aditya Gopalan; Gugan Thoppe (CoRR, 2022)

Actor-Critic based Improper Reinforcement Learning. - Mohammadi Zaki; Avinash Mohan; Aditya Gopalan; Shie Mannor (CoRR, 2022)

Sequential Multi-Hypothesis Testing in Multi-Armed Bandit Problems: An Approach for Asymptotic Optimality. - Gayathri R. Prabhu; Srikrishna Bhashyam; Aditya Gopalan; Rajesh Sundaresan (IEEE Trans. Inf. Theory, 2022)

Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. - Debangshu Banerjee 002; Avishek Ghosh; Sayak Ray Chowdhury; Aditya Gopalan (AISTATS, 2023)

Bregman Deviations of Generic Exponential Families. - Sayak Ray Chowdhury; Patrick Saux; Odalric Maillard; Aditya Gopalan (COLT, 2023)

WiROS: A QoS Software Solution for ros2 in a WiFi Network. - Bishal Jaiswal; Himanshu Tyagi; Aditya Gopalan; Vishal Sevani (COMSNETS, 2023)

On the Minimax Regret for Linear Bandits in a wide variety of Action Spaces. - Debangshu Banerjee 002; Aditya Gopalan (CoRR, 2023)

When are Bandits Robust to Misspecification? - Debangshu Banerjee 002; Aditya Gopalan (CoRR, 2023)

Data flow dissemination in a network. - Aditya Gopalan; Alexander L. Stolyar (Queueing Syst. Theory Appl., 2023)

A Unified Framework for Discovering Discrete Symmetries. - Pavan Karjol; Rohan Kashyap; Aditya Gopalan; A. P. Prathosh (AISTATS, 2024)

Model-Based Best Arm Identification for Decreasing Bandits. - Sho Takemori; Yuhei Umeda; Aditya Gopalan (AISTATS, 2024)

Testing the Feasibility of Linear Programs with Bandit Feedback. - Aditya Gangrade; Aditya Gopalan; Venkatesh Saligrama; Clayton Scott (ICML, 2024)

Towards Reliable Alignment: Uncertainty-aware RLHF. - Debangshu Banerjee 002; Aditya Gopalan (CoRR, 2024)

Reliable Critics: Monotonic Improvement and Convergence Guarantees for Reinforcement Learning. - Eshwar S. R; Gugan Thoppe; Aditya Gopalan; Gal Dalal (CoRR, 2025)

Towards Reliable, Uncertainty-Aware Alignment. - Debangshu Banerjee 002; Kintan Saha; Aditya Gopalan (CoRR, 2025)