| Randomized greedy sensor selection: Leveraging weak submodularity A Hashemi, M Ghasemi, H Vikalo, U Topcu IEEE Transactions on Automatic Control 66 (1), 199-212, 2020 | 51 | 2020 |
| A randomized greedy algorithm for near-optimal sensor scheduling in large-scale sensor networks A Hashemi, M Ghasemi, H Vikalo, U Topcu 2018 Annual American Control Conference (ACC), 1027-1032, 2018 | 38 | 2018 |
| Online active perception for partially observable Markov decision processes with limited budget M Ghasemi, U Topcu 2019 IEEE 58th Conference on Decision and Control (CDC), 6169-6174, 2019 | 25 | 2019 |
| Submodular observation selection and information gathering for quadratic models A Hashemi, M Ghasemi, H Vikalo, U Topcu International Conference on Machine Learning, 2653-2662, 2019 | 24 | 2019 |
| Maximum realizability for linear temporal logic specifications R Dimitrova, M Ghasemi, U Topcu Automated Technology for Verification and Analysis: 16th International …, 2018 | 23 | 2018 |
| Task-oriented active perception and planning in environments with partially known semantics M Ghasemi, E Bulgur, U Topcu International Conference on Machine Learning, 3484-3493, 2020 | 14 | 2020 |
| No-regret learning in dynamic Stackelberg games N Lauffer, M Ghasemi, A Hashemi, Y Savas, U Topcu IEEE Transactions on Automatic Control, 2023 | 10 | 2023 |
| Reactive synthesis with maximum realizability of linear temporal logic specifications R Dimitrova, M Ghasemi, U Topcu Acta Informatica 57, 107-135, 2020 | 9 | 2020 |
| Counterexamples for robotic planning explained in structured language L Feng, M Ghasemi, KW Chang, U Topcu 2018 IEEE International Conference on Robotics and Automation (ICRA), 7292-7297, 2018 | 9 | 2018 |
| Perception-aware point-based value iteration for partially observable Markov decision processes M Ghasemi, U Topcu | 8 | 2018 |
| Multiple Plans are Better than One: Diverse Stochastic Planning M Ghasemi, ES Crafts, B Zhao, U Topcu Proceedings of the International Conference on Automated Planning and …, 2021 | 6 | 2021 |
| Identifying sparse low-dimensional structures in Markov chains: a nonnegative matrix factorization approach M Ghasemi, A Hashemi, H Vikalo, U Topcu 2020 American Control Conference (ACC), 1093-1098, 2020 | 5 | 2020 |
| Online learning with implicit exploration in episodic Markov decision processes M Ghasemi, A Hashemi, H Vikalo, U Topcu 2021 American Control Conference (ACC), 1953-1958, 2021 | 4 | 2021 |
| On submodularity of quadratic observation selection in constrained networked sensing systems M Ghasemi, A Hashemi, U Topcu, H Vikalo 2019 American Control Conference (ACC), 4671-4676, 2019 | 4 | 2019 |
| No-Regret Learning with High-Probability in Adversarial Markov Decision Processes M Ghasemi, A Hashemi, H Vikalo, U Topcu Conference on Uncertainty in Artificial Intelligence (UAI), 2021 | 3 | 2021 |
| A Barrier Pair Method for Safe Human-Robot Shared Autonomy B He, M Ghasemi, U Topcu, L Sentis 2021 60th IEEE Conference on Decision and Control (CDC), 2854-2861, 2021 | 2 | 2021 |
| Formal Methods for Autonomous Systems T Wongpiromsarn, M Ghasemi, M Cubuktepe, G Bakirtzis, S Carr, ... arXiv preprint arXiv:2311.01258, 2023 | 1 | 2023 |
| On the Complexity and Approximability of Optimal Sensor Selection for Mixed-Observable Markov Decision Processes J Bhargav, M Ghasemi, S Sundaram 2023 American Control Conference (ACC), 3332-3337, 2023 | 1 | 2023 |
| Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning MH Ahmed, M Ghasemi International Conference on Artificial Intelligence and Statistics, 2755-2763, 2024 | | 2024 |
| Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders L Wei, MQ Elahi, M Ghasemi, M Kocaoglu Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Ufuk TopcuThe University of Texas at AustinVerified email at utexas.edu
