|
 | Up a level |
Sen, D and Prashanth, LA and Gopalan, A (2023) Adaptive Estimation of Random Vectors with Bandit Feedback: A Mean-Squared Error Viewpoint. In: UNSPECIFIED, pp. 180-181.
Takemori, S and Umeda, Y and Gopalan, A (2024) Model-Based Best Arm Identification for Decreasing Bandits. In: 27th International Conference on Artificial Intelligence and Statistics, AISTATS 2024, 2 May 2024through 4 May 2024, Valencia, pp. 1567-1575.
Karjol, P and Kashyap, R and Gopalan, A and Prathosh, AP (2024) A Unified Framework for Discovering Discrete Symmetries. In: International Conference on Artificial Intelligence and Statistics, AISTATS 2024, 2 May 2024through 4 May 2024, Valencia, pp. 793-801.
Jaiswal, B and Tyagi, H and Gopalan, A and Sevani, V (2023) WiROS: A QoS Software Solution for ros2 in a WiFi Network. In: 15th International Conference on COMmunication Systems and NETworkS, COMSNETS 2023, 3 - 8 January 2023, Bangalore, pp. 216-218.
Banerjee, D and Ghosh, A and Chowdhury, SR and Gopalan, A (2023) Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. In: 26th International Conference on Artificial Intelligence and Statistics, AISTATS 2023, 25 - 27 April 2023, Valencia, pp. 8233-8262.
Zaki, M and Mohan, A and Gopalan, A (2022) Improved Pure Exploration in Linear Bandits with No-Regret Learning. In: 31st International Joint Conference on Artificial Intelligence, IJCAI 2022, 23 - 2022, Vienna, pp. 3709-3715.
Gopalan, A and Lakshminarayanan, B and Saligrama, V (2021) Bandit Quickest Changepoint Detection. In: 35th Conference on Neural Information Processing Systems, NeurIPS 2021, 6 - 14 December 2021, Virtual, Online, pp. 29064-29073.
Dhanaprakaash, G and Jaiswal, B and Acharya, S and Kumar, A and Varman, AM and Shah, K and Gadde, MS and Mishra, S and Gopalan, A and Amrutur, B and Tyagi, H and Patil, P and Krishnapuram, R and Banerjee, SS and Sundaram, S (2021) Network Based Multi-Bot Awareness. In: 2021 International Conference on COMmunication Systems and NETworkS, COMSNETS 2021, 5-9 Jan 2021, Bangalore; India, pp. 138-139.
Saha, A and Gopalan, A (2020) Best-item Learning in Random Utility Models with Subset Choices. In: 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26 - 28 August 2020, pp. 4281-4291.
Shah, D and Choudhury, T and Karamchandani, N and Gopalan, A (2020) Sequential mode estimation with oracle queries. In: AAAI 2020 - 34th AAAI Conference on Artificial Intelligence, 7 February - 12 February 2020, New York, pp. 5644-5651.
Saha, A and Gopalan, A (2020) Active ranking with subset-wise preferences. In: 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16 - 18 April 2019, LOISIR Hotel NahaNaha; Japan.
Acharya, S and Bharadwaj, A and Simmhan, Y and Gopalan, A and Parag, P and Tyagi, H (2020) CORNET: A Co-Simulation Middleware for Robot Networks. In: 2020 International Conference on COMmunication Systems and NETworkS, 7-11 Jan 2020, Bengaluru;, pp. 245-251.
Saha, A and Gopalan, A (2020) From pac to instance-optimal sample complexity in the plackett-luce model. In: 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, pp. 8336-8345.
Jhunjhunwala, PR and Moharir, S and Manjunath, D and Gopalan, A (2019) On a class of restless multi-armed bandits with deterministic policies. In: 12th International Conference on Signal Processing and Communications, SPCOM 2018, 16 - 19 July 2018, Bangalore, pp. 487-491.
Chowdhury, SR and Gopalan, A (2019) Bayesian optimization under heavy-tailed payoffs. In: 33rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 8-14 December 2019, Vancouver; Canada.
Saha, A and Gopalan, A (2019) Combinatorial bandits with relative feedback. In: 33rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 8-14 December 2019, Vancouver; Canada.
Mohan, A and Gopalan, A and Kumar, A (2018) Reduced-State, Optimal Medium Access Control for Wireless Data Collection Networks. In: IEEE Conference on Computer Communications, INFOCOM 2018, 15 - 19 April 2018, Honolulu, pp. 567-575.
Saha, A and Gopalan, A (2018) Battle of bandits. In: 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018, 6 - 10 August 2018, Monterey, pp. 805-814.
Barman, S and Gopalan, A and Saha, A (2018) Online learning for structured loss spaces. In: 32nd AAAI Conference on Artificial Intelligence, AAAI 2018, 2 - 7 February 2018, New Orleans, pp. 2696-2703.
Chowdhury, SR and Gopalan, A (2017) On kernelized multi-armed bandits. In: 34th International Conference on Machine Learning, ICML 2017, 6 - 11 August 2017, Sydney, pp. 1397-1422.
Ghosh, A and Chowdhury, SR and Gopalan, A (2017) Misspecified linear bandits. In: 31st AAAI Conference on Artificial Intelligence, AAAI 2017, 4-10 February 2017, San Francisco, pp. 3761-3767.
Prabhu, GR and Bhashyam, S and Gopalan, A and Sundaresan, R (2022) Sequential Multi-Hypothesis Testing in Multi-Armed Bandit Problems: An Approach for Asymptotic Optimality. In: IEEE Transactions on Information Theory, 68 (7). pp. 4790-4817.
Gopalan, A and Tyagi, H (2020) How Reliable are Test Numbers for Revealing the COVID-19 Ground Truth and Applying Interventions? In: Journal of the Indian Institute of Science, 100 (4). pp. 863-884.
Mohan, A and Gopalan, A and Kumar, A (2020) Reduced-state, optimal scheduling for decentralized medium access control of a class of wireless networks. In: IEEE/ACM Transactions on Networking, 28 (3). pp. 1017-1032.
