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2020 – today
- 2024
[c6]Archana Bura
, Sarat Chandra Bobbili, Shreyas Rameshkumar, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai:
Structured Reinforcement Learning for Media Streaming at the Wireless Edge. MobiHoc 2024: 101-110- [i9]Archana Bura, Sarat Chandra Bobbili, Shreyas Rameshkumar, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai:
Structured Reinforcement Learning for Media Streaming at the Wireless Edge. CoRR abs/2404.07315 (2024) - [i8]Avisek Naug, Antonio Guillen, Ricardo Luna, Vineet Gundecha, Desik Rengarajan, Sahand Ghorbanpour, Sajad Mousavi, Ashwin Ramesh Babu, Dejan Markovikj, Lekhapriya Dheeraj Kashyap, Soumyendu Sarkar:
SustainDC - Benchmarking for Sustainable Data Center Control. CoRR abs/2408.07841 (2024) - 2023
- [i7]Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai:
Federated Ensemble-Directed Offline Reinforcement Learning. CoRR abs/2305.03097 (2023) - [i6]Sajad Mousavi, Ricardo Luna Gutiérrez, Desik Rengarajan, Vineet Gundecha, Ashwin Ramesh Babu, Avisek Naug, Antonio Guillen, Soumyendu Sarkar:
N-Critics: Self-Refinement of Large Language Models with Ensemble of Critics. CoRR abs/2310.18679 (2023) - 2022
- [j2]Archana Bura, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai, Jean-François Chamberland:
Learning to Cache and Caching to Learn: Regret Analysis of Caching Algorithms. IEEE/ACM Trans. Netw. 30(1): 18-31 (2022) - [j1]Rajarshi Bhattacharyya, Archana Bura, Desik Rengarajan, Mason Rumuly, Bainan Xia, Srinivas Shakkottai, Dileep Kalathil, Ricky K. P. Mok, Amogh Dhamdhere:
QFlow: A Learning Approach to High QoE Video Streaming at the Wireless Edge. IEEE/ACM Trans. Netw. 30(1): 32-46 (2022) - [c5]Desik Rengarajan, Gargi Vaidya, Akshay Sarvesh, Dileep M. Kalathil, Srinivas Shakkottai:
Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration. ICLR 2022 - [c4]Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai:
Enhanced Meta Reinforcement Learning via Demonstrations in Sparse Reward Environments. NeurIPS 2022 - [i5]Desik Rengarajan, Gargi Vaidya, Akshay Sarvesh, Dileep M. Kalathil, Srinivas Shakkottai:
Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration. CoRR abs/2202.04628 (2022) - [i4]Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai:
Enhanced Meta Reinforcement Learning using Demonstrations in Sparse Reward Environments. CoRR abs/2209.13048 (2022) - 2021
- [c3]Ki-Yeob Lee, Desik Rengarajan, Dileep M. Kalathil, Srinivas Shakkottai:
Reinforcement Learning for Mean Field Games with Strategic Complementarities. AISTATS 2021: 2458-2466 - 2020
- [i3]Archana Bura, Desik Rengarajan, Dileep M. Kalathil, Srinivas Shakkottai, Jean-François Chamberland-Tremblay:
Learning to Cache and Caching to Learn: Regret Analysis of Caching Algorithms. CoRR abs/2004.00472 (2020) - [i2]Ki-Yeob Lee, Desik Rengarajan, Dileep M. Kalathil, Srinivas Shakkottai:
Learning Trembling Hand Perfect Mean Field Equilibrium for Dynamic Mean Field Games. CoRR abs/2006.11683 (2020)
2010 – 2019
- 2019
- [c2]Rajarshi Bhattacharyya, Archana Bura, Desik Rengarajan, Mason Rumuly, Srinivas Shakkottai, Dileep M. Kalathil, Ricky K. P. Mok, Amogh Dhamdhere:
QFlow: A Reinforcement Learning Approach to High QoE Video Streaming over Wireless Networks. MobiHoc 2019: 251-260 - [i1]Rajarshi Bhattacharyya, Archana Bura, Desik Rengarajan, Mason Rumuly, Srinivas Shakkottai, Dileep M. Kalathil, Ricky K. P. Mok, Amogh Dhamdhere:
QFlow: A Reinforcement Learning Approach to High QoE Video Streaming over Wireless Networks. CoRR abs/1901.00959 (2019) - 2017
- [c1]Chirag Ramesh Srivatsa, Desik Rengarajan, Vamsi Krishna Tumuluru:
Modeling demand flexibility of electric vehicles. SmartGridComm 2017: 363-368
Coauthor Index
aka: Dileep Kalathil
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