Arnob Ghosh, Mehrdad Moharrami, ``Online Learning in Risk Sensitive Constrained MDP", Forty-Second International Conference on Machine Learning (ICML'2025), https://openreview.net/pdf?id=5s7D7FPuTc
Amirhossein Roknilamouki, Arnob Ghosh, Ming Shi, Fatemeh Nourzad, Eylem Ekici, Ness B Shroff, ``Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces", Forty-Second International Conference on Machine Learning (ICML'2025), https://openreview.net/pdf?id=sElAqKsJrQ
Deepak Vungarala, Mohammed Essa Elbtity, Kartik Pandit, Sumiya Syed, Sakila Alam, Arnob Ghosh, Ramtin Zand, Shaahin Angizi,``TPU-Gen: LLM-Driven Custom Tensor Processing Unit Generator", 1st IEEE International Conference on Language Aided Design, https://openreview.net/pdf?id=yKFEqLxAvU
Honghao Wei, Xiyue Peng, Arnob Ghosh, and Xin Liu, ``Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning", Thirty-Eighth Neural Information Processing Systems (NeurIPS'2024), https://openreview.net/forum?id=82Ndsr4OS6
Arnob Ghosh, Xingyu Zhou, and Ness Shroff, ``Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2024, pp. 1054--1062, https://proceedings.mlr.press/v238/ghosh24a.html
Deepak Vungarala, Sakila Alam, Arnob Ghosh and Shaahin Angizi, ``SPICEPilot: Navigating SPICE Code Generation and Simulation with AI Guidance", IEEE International Conference on Rebooting Computing (ICRC), 2024.
Arnob Ghosh, ``Sample Complexity for Obtaining Sub-optimality and Violation bound for Distributionally Robust Constrained MDP", First Reinforcement Learning Safety Workshop, 2024, https://openreview.net/pdf?id=T2XyWqN2dw
Peizhong Ju, Arnob Ghosh, and Ness Shroff, ``Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning", Twelfth International Conference on Learning Representation (ICLR'2024), https://arxiv.org/abs/2306.00324
Ubaid Qureshi, Arnob Ghosh, and B. K. Panigrahi. "Dynamic Routing and Scheduling of Mobile Charging Stations for Electric Vehicles Using Deep Reinforcement Learning." 2024 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2024. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10688695
Xinyue Hu, Arnob Ghosh, Xin Liu, Zhi-Li Zhang, and Ness Shroff, ``COREL: Constrained Reinforcement Learning for Video Streaming ABR Algorithm Design Over mmWave 5G", IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR), 2023, https://ieeexplore.ieee.org/abstract/document/10317803
Arnob Ghosh, ``Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation", in Learning for Decision and Control (L4DC), 2023, PMLR, pp.1112-1124, https://proceedings.mlr.press/v211/ghosh23a.html
Honghao Wei, Arnob Ghosh, Ness Shroff, Lei Ying, and Xingyu Zhou, ``Provably Efficient Model-Free Algorithms for Non-stationary CMDPs", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2023, pp. 6527--6570, https://proceedings.mlr.press/v206/wei23b.html
Arnob Ghosh, Xingyu Zhou, and Ness Shroff, ``Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation", at the Eleventh International Conference on Learning Representation (ICLR), 2023, https://par.nsf.gov/servlets/purl/10441753.
U. Qureshi, Arnob Ghosh, and B. K. Panigrahi, "Dynamic Pricing Based Mobile Charging Service for Electric Vehicle Charging," 2023 IEEE 3rd International Conference on Sustainable Energy and Future Electric Transportation (SEFET), Bhubaneswar, India, 2023
Arnob Ghosh, Xingyu Zhou, and Ness Shroff, `` Provably Efficient Safe Model-free Reinforcement Learning with Linear Function Approximation”, Accepted at the Thirty-Sixth Neural Information Processing System (NeurIPS’22), https://arxiv.org/pdf/2206.11889.pdf.
Yuntian Deng, Xingyu Zhou, Arnob Ghosh, Abhishek Gupta, and Ness Shroff, “Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits”, Accepted in 20th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), (Runnerup for the best Student Paper Award) Turin, Italy, Sept. 2022. https://arxiv.org/pdf/2207.00908.pdf
Arnob Ghosh, and Randall Berry, “Competition among Ride Service Providers with Autonomous Vehicles”, Accepted in 20th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Turin, Italy, Sept. 2022.
Erica Salvato, Arnob Ghosh, Gianfranco Fenu, and Thomas Parisini. “Control of a Mixed Autonomy Signalised Urban Intersection: An Event-Driven Reinforcement Learning Approach”, in IEEE American Control Conference (ACC’22), pp. 3285-3290.
Arnob Ghosh, Matteo Scandela, Michelangelo Bin, and Thomas Parisini, “Traffic-Light Control at Urban Intersections Using Expected Waiting-Time Information”, 60th IEEE Conference on Decision and Control (CDC), 2021, pp. 1953-1959.
Erica Salvato, Arnob Ghosh, Gianfranco Fenu, and Thomas Parisini, ``Control of a Mixed Autonomy Signalised Urban Intersection: An Action-Delayed Reinforcement Learning Approach,” 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 2042-2047,
Diptangshu Sen, and Arnob Ghosh, “Prospect-Theoretic Analysis for Selling back Energies to the Grid”, in, IEEE Proceedings of European Control Conference (ECC’21), pp. 842-847.
Abubakr Al-Abbasi, Arnob Ghosh, and Vaneet Aggarwal, ``DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning", accepted in 30th International Conference on Automated Planning and Scheduling (ICAPS), Journal Track, (Acceptance Rate: 21%), October 2020.
Arnob Ghosh, and Randall Berry, ``Entry and Investment in CBRS Shared Spectrum", 18th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOPT), Volos, Greece, June 2020, pp. 1-8.
Arnob Ghosh, and Randall Berry, ``Spot Markets for Spectrum Measurements", in IEEE Proceedings on Dynamic Spectrum Access (DySpan), November, 2019, pp. 1-10.
Arnob Ghosh, and Randall Berry, ``Competition with Three-Tier Spectrum Access and Spectrum Monitoring", to appear in Proceedings of ACM MobiHoc' 2019, (Acceptance Rate: 20 %) , Catania, Italy.
Arnob Ghosh, Randall Berry, and Vaneet Aggarwal,`` Spectrum Measurement Market for Licensed Band in CBRS", in Proceedings of International Conference on NETwork, Games, COntrol and oPtimization (NETGCOOP), 2018.
Arnob Ghosh, and Vaneet Aggarwal, ``Menu-Based Pricing for Profitable Electric Vehicle Charging with Vehicle-to-Grid Service", in International Symposium on Signal Processing and Communication (SPCOM'18), pp. 1-6, 2018.
Arnob Ghosh, Randall Berry, and Vaneet Aggarwal, ``Spectrum Measurement Markets for Tiered Spectrum Access", in IEEE International Conference on Communications (ICC), 2018, pp.1-6, Kansas City.
Arnob Ghosh, and Vaneet Aggarwal, ``Electric Vehicle Charging with Menu-Based Pricing," in Proc. IEEE ICC (SAC Symposium Communications for the Smart Grid, May 2017, Paris.
Arnob Ghosh, Saswati Sarkar, and Randall Berry,''Secondary Spectrum Market: To Acquire or not to acquire side-information?", 2016 IEEE International Symposium on Information Theory (ISIT), Barcelona, 2016, pp. 1636-1640. (View)
Arnob Ghosh, and Saswati Sarkar,``Secondary Spectrum Oligopoly Market over large locations", presented in Information Theory and Applications (ITA), February 2016. (View)
Arnob Ghosh, Laura Cottatelucci, and Eitan Altman, "Nash Equilibrium for Femto Cell Power Allocation in Hetnets with channel uncertainty", presented in 2015 IEEE Global Communications Conference (GLOBECOM'15), San Diego, pp. 1-7. (View)
Arnob Ghosh, and Saswati Sarkar," Pricing for profit in Internet of Things", in IEEE International Symposium on Information Theory (ISIT), Hong Kong, 2015, pp. 2211--2215. (View)
Arnob Ghosh , Laura Cottatellucci, and Eitan Altman,"Normalized Nash Equilibrium for Power Allocation among femto-Base Stations in Heterogeneous Network", presented in 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2015, Mumbai.
Arnob Ghosh and Saswati Sarkar, "Quality Sensitive Price Competition in Spectrum Oligopoly over Multiple locations", In IEEE proceedings of 48th Annual Conference on Information Sciences and Systems (CISS), pp. 1--6, 2014.View
Piotr Wieck, Eitan Altman and Arnob Ghosh, "Mean-field Game approach to Admission control in M/M/$\infty$ Queue with Decreasing Congestion Cost", In IEEE proceedings of International Conference on NETwork, Games, COntrol and oPtimization (NETGCOOP), 2014.View
Arnob Ghosh and Saswati Sarkar, "Quality Sensitive Price Competition in Spectrum Oligopoly", IEEE International Symposium on Information Theory (ISIT) 2013, Istanbul, pp. 2770-2774, 2013. View