Niao He

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Semih Cayci

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Publications

2024
[j10]
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Semih Cayci, Niao He, R. Srikant:
Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation. SIAM J. Optim. 34(3): 2729-2755 (2024)
[j9]
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  - journals/tmlr/CayciH024
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Semih Cayci, Niao He, R. Srikant:
Finite-Time Analysis of Entropy-Regularized Neural Natural Actor-Critic Algorithm. Trans. Mach. Learn. Res. 2024 (2024)
2023
[j6]
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  - journals/tac/CayciSHS23
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Semih Cayci, Siddhartha Satpathi, Niao He, R. Srikant:
Sample Complexity and Overparameterization Bounds for Temporal-Difference Learning With Neural Network Approximation. IEEE Trans. Autom. Control. 68(5): 2891-2905 (2023)
[c41]
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  - conf/icml/YardimCGH23
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Batuhan Yardim, Semih Cayci, Matthieu Geist, Niao He:
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games. ICML 2023: 39722-39754
2022
[i36]
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  - journals/corr/abs-2202-09753
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Semih Cayci, Niao He, R. Srikant:
Learning to Control Partially Observed Systems with Finite Memory. CoRR abs/2202.09753 (2022)
[i30]
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  - journals/corr/abs-2206-00833
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Semih Cayci, Niao He, R. Srikant:
Finite-Time Analysis of Entropy-Regularized Neural Natural Actor-Critic Algorithm. CoRR abs/2206.00833 (2022)
[i27]
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  - journals/corr/abs-2212-14449
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Batuhan Yardim, Semih Cayci, Matthieu Geist, Niao He:
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games. CoRR abs/2212.14449 (2022)
2021
[i26]
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  - journals/corr/abs-2103-01391
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Semih Cayci, Siddhartha Satpathi, Niao He, R. Srikant:
Sample Complexity and Overparameterization Bounds for Projection-Free Neural TD Learning. CoRR abs/2103.01391 (2021)
[i23]
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  - journals/corr/abs-2106-04096
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Semih Cayci, Niao He, R. Srikant:
Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation. CoRR abs/2106.04096 (2021)

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