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Yunzhe Zhou

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2020 – today

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2024
[j1]
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  - journals/ml/ZhouXH24
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Yunzhe Zhou, Peiru Xu, Giles Hooker:
A generic approach for reproducible model distillation. Mach. Learn. 113(10): 7645-7688 (2024)
[i6]
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  - journals/corr/abs-2411-02221
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Xiaohan Wang, Yunzhe Zhou, Giles Hooker:
Targeted Learning for Variable Importance. CoRR abs/2411.02221 (2024)
2023
[c1]
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  - conf/aistats/ZhouQSL23
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Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li:
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. AISTATS 2023: 6704-6721
[i5]
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  - journals/corr/abs-2305-19244
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Yunzhe Zhou, Chengchun Shi, Lexin Li, Qiwei Yao:
Testing for the Markov Property in Time Series via Deep Conditional Generative Learning. CoRR abs/2305.19244 (2023)
2022
[i4]
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  - journals/corr/abs-2209-00147
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Indrayudh Ghosal, Yunzhe Zhou, Giles Hooker:
The Infinitesimal Jackknife and Combinations of Models. CoRR abs/2209.00147 (2022)
[i3]
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  - journals/corr/abs-2210-14420
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Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li:
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. CoRR abs/2210.14420 (2022)
[i2]
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  - journals/corr/abs-2211-12631
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Yunzhe Zhou, Peiru Xu, Giles Hooker:
A Generic Approach for Statistical Stability in Model Distillation. CoRR abs/2211.12631 (2022)
2021
[i1]
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  - journals/corr/abs-2106-01474
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Chengchun Shi, Yunzhe Zhou, Lexin Li:
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning. CoRR abs/2106.01474 (2021)

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