OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
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Showing 21 citing articles:
Constrained Deep Reinforcement Learning for Energy Sustainable Multi-UAV Based Random Access IoT Networks With NOMA
Sami Khairy, Prasanna Balaprakash, Lin X. Cai, et al.
IEEE Journal on Selected Areas in Communications (2020) Vol. 39, Iss. 4, pp. 1101-1115
Open Access | Times Cited: 81
Sami Khairy, Prasanna Balaprakash, Lin X. Cai, et al.
IEEE Journal on Selected Areas in Communications (2020) Vol. 39, Iss. 4, pp. 1101-1115
Open Access | Times Cited: 81
Risk Averse Robust Adversarial Reinforcement Learning
Xinlei Pan, Daniel Seita, Yang Gao, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 8522-8528
Open Access | Times Cited: 59
Xinlei Pan, Daniel Seita, Yang Gao, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 8522-8528
Open Access | Times Cited: 59
Optimizing Coverage and Capacity in Cellular Networks using Machine Learning
Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2021), pp. 8138-8142
Open Access | Times Cited: 54
Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2021), pp. 8138-8142
Open Access | Times Cited: 54
Quantitative Trading on Stock Market Based on Deep Reinforcement Learning
Jia Wu, Chen Wang, Lidong XIONG, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2019), pp. 1-8
Closed Access | Times Cited: 32
Jia Wu, Chen Wang, Lidong XIONG, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2019), pp. 1-8
Closed Access | Times Cited: 32
Risk-sensitive reinforcement learning
Nelson Vadori, Sumitra Ganesh, Prashant Reddy, et al.
(2020), pp. 1-9
Open Access | Times Cited: 26
Nelson Vadori, Sumitra Ganesh, Prashant Reddy, et al.
(2020), pp. 1-9
Open Access | Times Cited: 26
Zeroth-Order Stochastic Compositional Algorithms for Risk-Aware Learning
Dionysios S. Kalogerias, Warren B. Powell
SIAM Journal on Optimization (2022) Vol. 32, Iss. 2, pp. 386-416
Open Access | Times Cited: 10
Dionysios S. Kalogerias, Warren B. Powell
SIAM Journal on Optimization (2022) Vol. 32, Iss. 2, pp. 386-416
Open Access | Times Cited: 10
Distributional Soft Actor Critic for Risk Sensitive Learning.
Xiaoteng Ma, Qiyuan Zhang, Li Xia, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 12
Xiaoteng Ma, Qiyuan Zhang, Li Xia, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 12
Improving Robustness via Risk Averse Distributional Reinforcement Learning
Rahul Singh, Qinsheng Zhang, Yongxin Chen
arXiv (Cornell University) (2020)
Open Access | Times Cited: 10
Rahul Singh, Qinsheng Zhang, Yongxin Chen
arXiv (Cornell University) (2020)
Open Access | Times Cited: 10
Learning a Low-Dimensional Representation of a Safe Region for Safe Reinforcement Learning on Dynamical Systems
Zhehua Zhou, Ozgur S. Oguz, Marion Leibold, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 34, Iss. 5, pp. 2513-2527
Open Access | Times Cited: 8
Zhehua Zhou, Ozgur S. Oguz, Marion Leibold, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 34, Iss. 5, pp. 2513-2527
Open Access | Times Cited: 8
Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic
Yangang Ren, Jingliang Duan, Shengbo Eben Li, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 7
Yangang Ren, Jingliang Duan, Shengbo Eben Li, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 7
Optimizing Coverage and Capacity in Cellular Networks using Machine Learning.
Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 5
Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 5
A Convex Programming Approach to Data-Driven Risk-Averse Reinforcement Learning
Yuzhen Han, Majid Mazouchi, Subramanya Nageshrao, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 4
Yuzhen Han, Majid Mazouchi, Subramanya Nageshrao, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 4
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
Yingjie Fei, Zhuoran Yang, Yudong Chen, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 3
Yingjie Fei, Zhuoran Yang, Yudong Chen, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 3
Risk-Aware MMSE Estimation
Dionysios S. Kalogerias, Luiz F. O. Chamon, George J. Pappas, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 2
Dionysios S. Kalogerias, Luiz F. O. Chamon, George J. Pappas, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 2
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
Chris Cundy, Stefano Ermon
arXiv (Cornell University) (2020)
Open Access | Times Cited: 2
Chris Cundy, Stefano Ermon
arXiv (Cornell University) (2020)
Open Access | Times Cited: 2
A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes
Sami Khairy, Prasanna Balaprakash, Lin X. Cai
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 12, pp. 18914-18921
Open Access
Sami Khairy, Prasanna Balaprakash, Lin X. Cai
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 12, pp. 18914-18921
Open Access
Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning (Extended Abstract)
Yifan Zhang, Peilin Zhao, Qingyao Wu, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 3771-3772
Closed Access
Yifan Zhang, Peilin Zhao, Qingyao Wu, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 3771-3772
Closed Access
Risk-Constrained Linear-Quadratic Regulators
Anastasios Tsiamis, Dionysios S. Kalogerias, Luiz F. O. Chamon, et al.
arXiv (Cornell University) (2020)
Closed Access
Anastasios Tsiamis, Dionysios S. Kalogerias, Luiz F. O. Chamon, et al.
arXiv (Cornell University) (2020)
Closed Access
Heuristics based on projection occupation measures for probabilistic planning with dead-ends and risk
Milton Raúl Condori Fernández
(2020)
Open Access
Milton Raúl Condori Fernández
(2020)
Open Access
Reinforcement Learning Beyond Expectation.
Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark, et al.
arXiv (Cornell University) (2021)
Closed Access
Bhaskar Ramasubramanian, Luyao Niu, Andrew Clark, et al.
arXiv (Cornell University) (2021)
Closed Access
Likelihood ratio-based policy gradient methods for distorted risk measures: A non-asymptotic analysis.
Nithia Vijayan, L. A. Prashanth
arXiv (Cornell University) (2021)
Closed Access
Nithia Vijayan, L. A. Prashanth
arXiv (Cornell University) (2021)
Closed Access
