Aditya Gopalan

Gayathri R Prabhu, Srikrishna Bhashyam, Aditya Gopalan and Rajesh Sundaresan, Sequential Multi-hypothesis Testing in Multi-armed Bandit Problems: An Approach for Asymptotic Optimality. [arXiv]
IEEE Transactions on Information Theory, 2022 (to appear).

Aditya Gopalan and Himanshu Tyagi, How Reliable are Test Numbers for Revealing the COVID-19 Ground Truth and Applying Interventions? [view online]
Journal of the Indian Institute of Science, Vol. 100 No. 4 Oct. 2020 Issue on Digital Health, Guest Editor: Vijay Chandru, 2020.

Avinash Mohan, Aditya Gopalan and Anurag Kumar, Reduced-State, Optimal Scheduling for Decentralized Medium Access Control of a Class of Wireless Networks.
IEEE/ACM Transactions on Networking, Vol. 28, Issue 3, 2020.

Ravi Kumar Kolla, Krishna Jagannathan and Aditya Gopalan, Collaborative Learning of Stochastic Bandits over a Social Network. [PDF]
IEEE Transactions on Networking, Vol. 26 Issue 4, 2018. DOI: 10.1109/TNET.2018.2852361.

Rahul Meshram, D. Manjunath and Aditya Gopalan, On the Whittle Index for Restless Multi-armed Hidden Markov Bandits. [PDF]
IEEE Transactions on Automatic Control, 2018 (DOI: 10.1109/TAC.2018.2799521).

Aditya Gopalan, Constantine Caramanis, and Sanjay Shakkottai, Wireless Scheduling with Partial Information: Large Deviations and Optimality. [arXiv]
Queueing Systems, Volume 80 Issue 4, August 2015, pages 293-340 (DOI: 10.1007/s11134-015-9439-9).

Siddhartha Banerjee, Aditya Gopalan, Abhik Kumar Das, and Sanjay Shakkottai, Epidemic Spreading with External Agents. [PDF]
IEEE Transactions on Information Theory, Volume 60, Issue 7, 2014, pages 4125-4138.

Aditya Gopalan, Constantine Caramanis, and Sanjay Shakkottai, On the Value of Coordination and Delayed Queue Information in Multicellular Scheduling. [PDF]
IEEE Transactions on Automatic Control, Vol. 58(6), June 2013.

Akula Aneesh Reddy, Siddhartha Banerjee, Aditya Gopalan, Sanjay Shakkottai, and Lei Ying, On Distributed Scheduling with Heterogeneously Delayed Network-State Information. [PDF]
Queueing Systems: Theory and Applications (QUES), Special Issue on Wireless Communication Networks, Vol. 72, June 2012.

Aditya Gopalan, Constantine Caramanis, and Sanjay Shakkottai, On Wireless Scheduling with Partial Channel-State Information. [PDF]
IEEE Transactions on Information Theory, Vol. 58(1), January 2012.

Sho Takemori, Yuhei Umeda and Aditya Gopalan, Model-Based Best Arm Identification for Decreasing Bandits. [arXiv]
27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.

Pavan Karjol, Rohan Kashyap, Aditya Gopalan and Prathosh AP, A Unified Framework for Discovering Discrete Symmetries. [arXiv]
27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.

Sayak Ray Chowdhury, Patrick Saux, Odalric-Ambrym Maillard and Aditya Gopalan, Bregman Deviations of Generic Exponential Families. [arXiv]
36th Annual Conference on Learning Theory (COLT 2023), 2023.

Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury and Aditya Gopalan, Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. [arXiv]
26th International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.

Mohammadi Zaki, Avi Mohan, Aditya Gopalan and Shie Mannor, Actor-Critic based Improper Reinforcement Learning. [arXiv]
39th International Conference on Machine Learning (ICML), 2022.

Mohammadi Zaki, Avi Mohan and Aditya Gopalan, Improved Pure Exploration in Linear Bandits with No-Regret Learning. [arXiv]
31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.

Aditya Gopalan, Braghadeesh Lakshminarayanan and Venkatesh Saligrama, Bandit Quickest Changepoint Detection. [arXiv]
35th Conference on Neural Information Processing Systems (NeurIPS), 2021.

Mohammadi Zaki, Avinash Mohan, Aditya Gopalan and Shie Mannor, Better than the Best: Gradient-based Improper Reinforcement Learning for Network Scheduling. [arXiv]
Reinforcement Learning in Networks and Queues workshop at ACM SIGMETRICS, 2021.

Sayak Ray Chowdhury, Aditya Gopalan and Odalric Maillard, Reinforcement Learning in Parametric MDPs with Exponential Families.
24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.

Sayak Ray Chowdhury and Aditya Gopalan, No-regret Algorithms for Multi-task Bayesian Optimization.
24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.

Mohammadi Zaki, Avinash Mohan and Aditya Gopalan, Employing No Regret Learners for Pure Exploration in Linear Bandits.
12th OPT Workshop on Optimization for Machine Learning (OPT2020) at the conference on Neural Information Processing Systems, 2020.

Aadirupa Saha and Aditya Gopalan, From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model.
37th International Conference on Machine Learning (ICML), 2020.

Aadirupa Saha and Aditya Gopalan, Best-item Learning in Random Utility Models with Subset Choices.
23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

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

Srikrishna Acharya, Bharadwaj Amrutur, Yogesh Simmhan, Aditya Gopalan, Parimal Parag and Himanshu Tyagi, CORNET: A Co-Simulation Middleware for Robot Networks.
2020 International Conference on COMmunication Systems & NETworkS (COMSNETS), 2020.

Dhruti Shah, Tuhinangshu Choudhury, Nikhil Karamchandani and Aditya Gopalan, Sequential Mode Estimation with Oracle Queries.
34th AAAI Conference on Artificial Intelligence (AAAI 2020), 2020.

Siddharth Mitra and Aditya Gopalan, On Adaptivity in Information-constrained Online Learning.
34th AAAI Conference on Artificial Intelligence (AAAI 2020), 2020.

Sayak Ray Chowdhury and Aditya Gopalan, Bayesian Optimization under Heavy-tailed Payoffs.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 2019.

Aadirupa Saha and Aditya Gopalan, Combinatorial Bandits with Relative Feedback.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 2019.

Gayathri R Prabhu, Srikrishna Bhashyam, Aditya Gopalan and Rajesh Sundaresan, Learning to Detect an Anomalous Target with Observations from an Exponential Family.
The 2nd IEEE Data Science Workshop (DSW 2019), 2019.

Aadirupa Saha and Aditya Gopalan, PAC Battling Bandits in the Plackett-Luce Model.
30th International Conference on Algorithmic Learning Theory (ALT), 2019.

Sayak Ray Chowdhury and Aditya Gopalan, Online Learning in Kernelized Markov Decision Processes.
22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.

Aadirupa Saha and Aditya Gopalan, Active Ranking with Subset-wise Preferences.
22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.

Aditya Gopalan, No-regret Reinforcement Learning.
Indian Control Conference, 2019.

Sayak Ray Chowdhury and Aditya Gopalan, Online Learning in Kernelized Markov Decision Processes.
Infer to Control: Probabilistic Reinforcement Learning and Structured Control workshop, Neural Information Processing Systems, 2018.

Sayak Ray Chowdhury and Aditya Gopalan, On Batch Bayesian Optimization.
All of Bayesian Nonparametrics workshop, Neural Information Processing Systems, 2018.

Aadirupa Saha and Aditya Gopalan, Battle of Bandits. [PDF]
Conference on Uncertainty in Artificial Intelligence (UAI), 2018.

Prakirt Raj Jhunjhunwala, Sharayu Moharir, D. Manjunath and Aditya Gopalan, On a Class of Restless Multi-armed Bandits with Deterministic Policies.
International Conference on Signal Processing and Communications (SPCOM), 2018.

Avinash Mohan, Aditya Gopalan and Anurag Kumar, Reduced-State, Optimal Medium Access Control for Wireless Data Collection Networks. [PDF]
IEEE INFOCOM, 2018.

Siddharth Barman, Aditya Gopalan and Aadirupa Saha, Online Learning for Structured Loss Spaces.
AAAI Conference on Artificial Intelligence (AAAI), 2018.

Sayak Ray Chowdhury and Aditya Gopalan, On Kernelized Multi-armed Bandits. [ArXiv]
Proc. International Conference on Machine Learning (ICML), 2017.

Parth Thaker, Aditya Gopalan and Rahul Vaze, When to Arrive in a Congested System: Achieving Equilibrium via Learning Algorithm.
The 2017 International Workshop on Resource Allocation, Cooperation and Competition in Wireless Networks (RAWNET), WiOpt 2017, Paris, France.

Aditya Gopalan, Prashanth L.A., Michael Fu and Steven I. Marcus, Weighted bandits or: How bandits learn distorted values that are not expected.
AAAI Conference on Artificial Intelligence (AAAI), 2017.

Avishek Ghosh, Sayak Ray Chowdhury and Aditya Gopalan, Misspecified Linear Bandits.
AAAI Conference on Artificial Intelligence (AAAI), 2017.

Rahul Meshram, Aditya Gopalan and D. Manjunath, Restless bandits that hide their hand and recommendation systems.
9th International Conference on Communication Systems and Networks (COMSNETS), 2017.

Ravi Kumar Kolla, Krishna Jagannathan and Aditya Gopalan, Collaborative Learning of Stochastic Bandits over a Social Network.
54th Annual Allerton Conference on Communication, Control, and Computing, Univ. of Illinois at Urbana-Champaign (USA), 2016.

Rahul Meshram, D. Manjunath and Aditya Gopalan, Optimal Recommendation to Users that React: Online Learning for a Class of POMDPs.
Proc. IEEE Conference on Decision and Control (CDC), Las Vegas (USA), 2016.

Andrew Newell, Gabriel Kliot, Ishai Menache, Aditya Gopalan and Mark Silberstein, Optimizing Distributed Actor Systems for Dynamic Interactive Services.
Proc. European Conference on Computer Systems (EuroSys 2016), London (UK), 2016.

Shivaram Kalyanakrishnan, Neeldhara Misra and Aditya Gopalan, Randomised Procedures for Initialising and Switching Actions in Policy Iteration. [PDF]
Proc. 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix (USA), 2016.

Rahul Meshram, D. Manjunath and Aditya Gopalan, A Restless Bandit With No Observable States for Recommendation Systems and Communication Link Scheduling. [PDF]
Proc. IEEE Conference on Decision and Control (CDC), Osaka (Japan), 2015.

Aditya Gopalan and Shie Mannor, Thompson Sampling for Learning Parameterized Markov Decision Processes. [arXiv]
Proc. Conference on Learning Theory (COLT), Paris (France), 2015.

Abhinav Kumar, Sibi Raj B. Pillai, Rahul Vaze, and Aditya Gopalan, Optimal WiFi Sensing via Dynamic Programming.
The 2015 International Workshop on Resource Allocation, Cooperation and Competition in Wireless Networks (RAWNET), WiOpt 2015, Mumbai, India.

Aditya Gopalan, Shie Mannor, and Yishay Mansour, Thompson Sampling for Complex Online Problems. [PDF]
Proc. International Conference on Machine Learning (ICML), Beijing, June 2014.

Aditya Gopalan, Shie Mannor, and Yishay Mansour, Complex Bandit Problems and Thompson Sampling. [PDF]
First Multidisciplinary Conference on Reinforcement Learning and Decision Making, Princeton, NJ, USA, October 2013.

Aditya Gopalan, Constantine Caramanis, and Sanjay Shakkottai, Low-Delay Wireless Scheduling with Partial Channel-state Information. [PDF]
Proceedings of the 31st IEEE International Conference on Computer Communications (IEEE INFOCOM), Orlando, March 2012.

Ioannis Mitliagkas, Aditya Gopalan, Constantine Caramanis, and Sriram Viswanath, User Rankings from Comparisons: Learning Permutations in High Dimensions. [PDF]
Proceedings of the 49th Allerton Conference on Communication, Control, and Computing, Urbana, IL, September 2011.

Aditya Gopalan, Siddhartha Banerjee, Abhik Kumar Das, and Sanjay Shakkottai, Random Mobility and the Spread of Infection. [PDF]
Proceedings of the 30th IEEE International Conference on Computer Communications (IEEE INFOCOM), Shanghai, April 2011.

Akula Aneesh Reddy, Siddhartha Banerjee, Aditya Gopalan, Sanjay Shakkottai, and Lei Ying, Wireless Scheduling with Heterogeneously Delayed Network-State Information. [PDF]
Proceedings of the 48th Allerton Conference on Communication, Control, and Computing, Urbana, IL, September 2010.

Aditya Gopalan, Constantine Caramanis , and Sanjay Shakkottai, On Wireless Scheduling with Partial Channel-State Information. [PDF]
Proceedings of the 45th Allerton Conference on Communication, Control, and Computing, Urbana, IL, September 2007.

Aditya Gopalan and Srikrishna Bhashyam, A Multiple Lattice Reduction Based Detector for Space Time Block Codes based on Cyclotomic Extensions.
Proceedings of the 44th Allerton Conference on Communication, Control, and Computing, Urbana, IL, August 2006.

Aditya Gopalan, Odalric-Ambrym Maillard and Mohammadi Zaki, Low-rank Bandits with Latent Mixtures [arXiv]
Tech. Report, 2016.

Aditya Gopalan, Thompson Sampling for Online Learning with Linear Experts [arXiv]
Tech. Report, 2013.