2025

  • Vishnu Saj, Bochan Lee, Dileep Kalathil, and Moble Benedict. “Robust Reinforcement Learning Control for Vision-Based Ship Landing of VTOL-UAVs.” Journal of the American Helicopter Society, 2025.

  • Muthirayan, Deepan, Dileep Kalathil, and Pramod P. Khargonekar. “Meta-learning online control for linear dynamical systems.” IEEE Transactions on Automatic Control, 2025.

  • Zaiyan Xu, Sushil Vemuri, Kishan Panaganti, Dileep Kalathil, Rahul Jain, and Deepak Ramachandran. “Distributionally Robust Direct Preference Optimization.” arXiv preprint arXiv:2502.01930, 2025.

  • Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena, Dheeraj Narasimha, Srinivas Shakkottai, Aditya Akella. “CONGO: Compressive Online Gradient Optimization.” In Proceedings of the 13th International Conference on Learning Representations (ICLR 2025), Apr. 2025.

  • Vishnu Teja Kunde, Vicram Rajagopalan, Chandra S. K. Valmeekam, Krishna R. Narayanan, Srinivas Shakkottai, Dileep Kalathil, Jean-François Chamberland. “Transformers are Provably Optimal In-context Estimators for Wireless Communications.” In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025), Apr. 2025.

  • S. K. Ankireddy, H. Kim, and K. R. Narayanan. “LIGHTCODE: Light Analytical and Neural Codes for Channels with Feedback.” IEEE Journal on Selected Areas in Communications, to appear in vol. 43, 2025.

  • W.-Y. Zhao, H.-Y. Chen, T. Liu, R. Tuo, and C. Tian. “From deep additive kernel learning to last-layer Bayesian neural networks via induced prior approximation.” In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025), Apr. 2025.

  • Chao Tian, Jun Chen, Krishna Narayanan. “Source-Channel Separation Theorems for Distortion Perception Coding”, arXiv preprint arXiv:2501.17706, 2025.

  • Yu-Shin Huang, Chao Tian, Krishna Narayanan, Lizhong Zheng. “Relatively-Secure LLM-Based Steganography via Constrained Markov Decision Processes”, arXiv preprint arXiv:2502.01827, 2025.

2024

  • ​Menati, Ali, Fatemeh Doudi, Dileep Kalathil, and Le Xie. “PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power Systems.” arXiv preprint arXiv:2412.06112, 2024.

  • ​Archana Bura, Sarat Chandra Bobbili, Shreyas Rameshkumar, Desik Rengarajan, Dileep Kalathil, and Srinivas Shakkottai. “Structured Reinforcement Learning for Media Streaming at the Wireless Edge.” In Proceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, pp. 101-110. 2024.

  • ​Archana Bura, Ushasi Ghosh, Dinesh Bharadia, and Srinivas Shakkottai. “Realtime Neural Whittle Indexing for Scalable Service Guarantees in NextG Cellular Networks.” In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking, 1823–1825, 2024.

  • Sapana Chaudhary, Ujwal Dinesha, Dileep Kalathil, Srinivas Shakkottai. “Risk‐Averse Finetuning of Large Language Models.” In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), Dec. 2024.

  • Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai. “Federated Ensemble-Directed Offline Reinforcement Learning.” In Advances in Neural Information Processing Systems 37 (NeurIPS 2024), Dec. 2024.

  • Amit Jena, Dileep Kalathil, Le Xie. “Meta‐Learning‐Based Adaptive Stability Certificates for Dynamical Systems.” In Proceedings of the AAAI Conference on Artificial Intelligence, Feb. 2024.

  • Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian. “Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation.” In Neural Information Processing Systems (NeurIPS 2023), Dec. 2023. (Presented in Dec. 2023, appeared 2024.)

  • Ruida Zhou, Chao Tian, and Tie Liu. “Exactly tight information-theoretic generalization error bound for the quadratic Gaussian problem.” IEEE Journal on Selected Areas in Information Theory, vol. 5, pp. 94–104, Mar. 2024.

  • Soumya Majumder, Lingzhi Dong, Fatemeh Doudi, Yuting Cai, Chao Tian, Dileep Kalathil, Keyu Ding, Anamitra Thatte, Na Li, and Le Xie. “Exploring the capabilities and limitations of large language models in the electric energy sector.” Joule, vol. 8, no. 6, pp. 1544–1549, June 2024.

  • Aayushman Sharma, Zirui Mao, Haiying Yang, Suman Chakravorty, Michael Demkowicz, Dileep Kalathil. “Optimal Control of Material Micro‐Structures.” ASME Journal of Dynamic Systems, Measurement, and Control, vol. 146, no. 11, Nov. 2024.

  • Dheeraj Narasimha, Dileep Kalathil, Srinivas Shakkottai. “Meta‐Learning for Fast Adaptation in Caching Networks.” IEEE/ACM Transactions on Networking, accepted Oct. 2024 (to appear).

  • Rongmei-Zhen Fan, Rui-da Zhou, Chao Tian, Xiaoning Qian. “Path-guided particle-based sampling.” In Proceedings of the 41st International Conference on Machine Learning (ICML 2024), July 2024.

  • Yi-Ning You, Rui-da Zhou, Jiaxin Park, Haoming Xu, Chao Tian, Zhi-Yuan Wang, and Yanfang (Fanny) Shen. “Latent 3D graph diffusion.” In Proceedings of the 12th International Conference on Learning Representations (ICLR 2024), May 2024.

  • Mingyan Cheng, Rui-da Zhou, Chao Tian, P. R. Kumar. “Provable policy gradient methods for average-reward Markov potential games.” In Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), May 2024.

  • Nidhi Sharma, Sayan Basu, Karthikeyan Shanmugam, Srinivas Shakkottai. “Bandits with mean bounds.” Transactions on Machine Learning Research (TMLR), accepted 2024.

  • Karthikeyan Shanmugam and Srinivas Shakkottai. “A Lyapunov Theory for Finite-Sample Guarantees of Markovian Bandits.” Transactions on Machine Learning Research (TMLR), Nov. 2024.

  • Sandesh Rao Mattu, Imran Ali Khan, Venkatesh Khammammetti, Beyza Dabak, Saif Khan Mohammed, Krishna Narayanan, Robert Calderbank. “Delay-Doppler Signal Processing with Zadoff-Chu Sequences”, arXiv preprint arXiv:2412.04295, 2024.

  • Patrick Agostini, Jean-Francois Chamberland, Federico Clazzer, Johannes Dommel, Gianluigi Liva, Andrea Munari, Krishna Narayanan, Yury Polyanskiy, Slawomir Stanczak, Zoran Utkovski. “Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple Access Perspective.” In 2024 IEEE Conference on Standards for Communications and Networking (CSCN), pp. 32–35, Nov. 2024.

  • Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan. “Sparse Regression LDPC Codes.” IEEE Transactions on Information Theory, Nov. 2024.

  • Yu-Shin Huang, Peter Just, Krishna Narayanan, Chao Tian. “OD-Stega: LLM-based near-imperceptible steganography via optimized distributions.” arXiv preprint arXiv:2410.04328, Oct. 2024.

  • Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan. “Multi-User SR-LDPC Codes.” arXiv preprint arXiv:2408.11165, Aug. 2024.

  • Bobak Nazer, Krishna Narayanan. “Computation Selection: Scheduling Users to Enable Over-the-Air Federated Learning.” In 2024 IEEE International Symposium on Information Theory (ISIT), pp. 1635–1640, July 2024.

  • Amit Jena, Dileep Kalathil, and Le Xie. “Meta-learning-based adaptive stability certificates for dynamical systems.” In Proceedings of the AAAI conference on artificial intelligence, vol. 38, no. 11, pp. 12801-12809. 2024.

  • Vasudev Gohil, Satwik Patnaik, Dileep Kalathil, and Jeyavijayan Rajendran. “AttackGNN:Red-Teaming GNNs in Hardware Security Using Reinforcement Learning.” In 33rd USENIX Security Symposium (USENIX Security 24), pp. 73-90. 2024.

  • ​An, Qing, Divyanshu Pandey, Rahman Doost-Mohammady, Ashutosh Sabharwal, and Srinivas Shakkottai. “Helix: A RAN Slicing Based Scheduling Framework for Massive MIMO Networks.” Proceedings of the ACM on Networking 2, no. CoNEXT4 (2024): 1-22.​

2023

  • Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh. “Bridging distributionally robust learning and offline rl: An approach to mitigate distribution shift and partial data coverage.” arXiv preprint arXiv:2310.18434, 2023.

  • Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh. “Distributionally robust behavioral cloning for robust imitation learning.” In 2023 62nd IEEE Conference on Decision and Control (CDC), pp. 1342-1347. IEEE, 2023.

  • Zaiyan Xu, Kishan Panaganti, Dileep Kalathil. “Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning.” In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), pp. 9728-9754. PMLR, 2023.

  • Ruida Zhou, Tao Liu, Dileep Kalathil, P. R. Kumar, Chao Tian. “Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation.” In Advances in Neural Information Processing Systems 36 (NeurIPS 2023), Dec. 2023.

  • Ting-Jui Chang, Sapana Chaudhary, Dileep Kalathil, Shahin Shahrampour. “Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-convex Problems.” Transactions on Machine Learning Research (TMLR), Oct. 2023.

  • Vasudev Gohil, Satwik Patnaik, Hao Guo, Dileep Kalathil, Jeyavijayan Rajendran. “DETERRENT: Detecting Trojans using Reinforcement Learning.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 42, no. 8, pp. 2058–2071, Aug. 2023.

  • Bochan Lee, Vishnu Saj, Moble Benedict, Dileep Kalathil. “Intelligent Vision-based Autonomous Ship Landing of VTOL UAVs.” Journal of the American Helicopter Society, vol. 68, no. 2, pp. 113–126, Apr. 2023.

  • Ruida Zhou, Chao Tian, Tie Liu. “Stochastic chaining and strengthened information-theoretic generalization bounds.” Journal of the Franklin Institute, vol. 360, no. 6, pp. 4114–4134, Apr. 2023.

  • Chao Tian, Hua Sun, and Jun Chen. “A Shannon-theoretic approach to the storage–retrieval trade-off in PIR systems.” Information (MDPI), vol. 14, no. 1, Article 44, Jan. 2023.

  • Chandra S. K. Valmeekam, Krishna R. Narayanan, Dileep Kalathil, Jean-François Chamberland, Srinivas Shakkottai. “LLMZip: Lossless Text Compression using Large Language Models.” arXiv preprint arXiv:2306.04050, June 2023.

  • Li Fan, Ruida Zhou, Chao Tian, Cong Shen. “Federated linear bandits with finite adversarial actions.” In Advances in Neural Information Processing Systems 36 (NeurIPS 2023), Dec. 2023.

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Patents

Full List of publications

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