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Shengyu Zhu 0001
Person information
- affiliation: Huawei Noah's Ark Lab, Hong Kong
- affiliation (PhD 2017): Syracuse University, NY, USA
Other persons with the same name
- Shengyu Zhu 0002
— Harbin Institute of Technology, School of Electronics and Information Engineering, China
- Shengyu Zhu 0003 — Ubiquant Investment, Beijing, China
- Shengyu Zhu 0004 — Google
- Shengyu Zhu 0005 — Institute of Control Engineering, Center for Development of Onboard Computers and Electronic Products, Beijing, China
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2020 – today
- 2024
- [j9]Shaokang Dong
WToE: Learning When to Explore in Multiagent Reinforcement Learning. IEEE Trans. Cybern. 54(8): 4789-4801 (2024) - [j8]Zhuangyan Fang
On Low-Rank Directed Acyclic Graphs and Causal Structure Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4924-4937 (2024) - [i20]Tim Tse, Zhitang Chen, Shengyu Zhu, Yue Liu:
Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms. CoRR abs/2401.18017 (2024) - 2023
- [j7]Ran Chen
A Unified Framework for Layout Pattern Analysis With Deep Causal Estimation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(4): 1199-1211 (2023) - [c18]Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He:
Conditional counterfactual causal effect for individual attribution. UAI 2023: 2519-2528 - 2022
- [j6]Zhuangyan Fang
A local method for identifying causal relations under Markov equivalence. Artif. Intell. 305: 103669 (2022) - [c17]Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu:
Out-of-distribution Generalization with Causal Invariant Transformations. CVPR 2022: 375-385 - [c16]Xiaopeng Zhang, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Evangeline F. Y. Young, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao:
RCANet: Root Cause Analysis via Latent Variable Interaction Modeling for Yield Improvement. ITC 2022: 100-107 - [c15]Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui:
ZIN: When and How to Learn Invariance Without Environment Partition? NeurIPS 2022 - [c14]Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Chen Yongwei:
Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates. NeurIPS 2022 - [c13]Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang:
Masked Gradient-Based Causal Structure Learning. SDM 2022: 424-432 - [c12]Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen:
Reframed GES with a neural conditional dependence measure. UAI 2022: 1782-1791 - [i19]Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen:
Universality of parametric Coupling Flows over parametric diffeomorphisms. CoRR abs/2202.02906 (2022) - [i18]Yan Lyu, Sunhao Dai, Peng Wu, Quanyu Dai, Yuhao Deng, Wenjie Hu, Zhenhua Dong, Jun Xu, Shengyu Zhu, Xiao-Hua Zhou:
A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. CoRR abs/2202.11351 (2022) - [i17]Yong Lin, Shengyu Zhu, Peng Cui:
ZIN: When and How to Learn Invariance by Environment Inference? CoRR abs/2203.05818 (2022) - [i16]Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu:
Out-of-distribution Generalization with Causal Invariant Transformations. CoRR abs/2203.11528 (2022) - [i15]Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen:
Reframed GES with a Neural Conditional Dependence Measure. CoRR abs/2206.08531 (2022) - [i14]Wenqian Li, Yinchuan Li, Shengyu Zhu, Yunfeng Shao, Jianye Hao, Yan Pang:
GFlowCausal: Generative Flow Networks for Causal Discovery. CoRR abs/2210.08185 (2022) - 2021
- [j5]Shengyu Zhu
Asymptotically Optimal One- and Two-Sample Testing With Kernels. IEEE Trans. Inf. Theory 67(4): 2074-2092 (2021) - [c11]Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao:
A Unified Framework for Layout Pattern Analysis with Deep Causal Estimation. ICCAD 2021: 1-9 - [c10]Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang:
Ordering-Based Causal Discovery with Reinforcement Learning. IJCAI 2021: 3566-3573 - [i13]Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang:
Ordering-Based Causal Discovery with Reinforcement Learning. CoRR abs/2105.06631 (2021) - [i12]Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan:
gCastle: A Python Toolbox for Causal Discovery. CoRR abs/2111.15155 (2021) - 2020
- [c9]Shengyu Zhu, Ignavier Ng, Zhitang Chen:
Causal Discovery with Reinforcement Learning. ICLR 2020 - [i11]Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He:
Low Rank Directed Acyclic Graphs and Causal Structure Learning. CoRR abs/2006.05691 (2020)
2010 – 2019
- 2019
- [c8]Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen:
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. AISTATS 2019: 1544-1553 - [i10]Shengyu Zhu, Zhitang Chen:
Causal Discovery with Reinforcement Learning. CoRR abs/1906.04477 (2019) - [i9]Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang:
Asymptotically Optimal One- and Two-Sample Testing with Kernels. CoRR abs/1908.10037 (2019) - [i8]Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse:
Causal Discovery by Kernel Intrinsic Invariance Measure. CoRR abs/1909.00513 (2019) - [i7]Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen:
Masked Gradient-Based Causal Structure Learning. CoRR abs/1910.08527 (2019) - [i6]Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang:
A Graph Autoencoder Approach to Causal Structure Learning. CoRR abs/1911.07420 (2019) - 2018
- [j4]Shengyu Zhu
Distributed Detection in Ad Hoc Networks Through Quantized Consensus. IEEE Trans. Inf. Theory 64(11): 7017-7030 (2018) - [i5]Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen:
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. CoRR abs/1802.07581 (2018) - [i4]Shengyu Zhu, Biao Chen, Zhitang Chen:
Exponentially Consistent Kernel Two-Sample Tests. CoRR abs/1802.08407 (2018) - 2017
- [j3]Shengyu Zhu
Corrections to "Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers". IEEE Trans. Signal Process. 65(6): 1638-1639 (2017) - 2016
- [j2]Shengyu Zhu, Biao Chen:
Quantized Consensus by the ADMM: Probabilistic Versus Deterministic Quantizers. IEEE Trans. Signal Process. 64(7): 1700-1713 (2016) - [c7]Shengyu Zhu, Mingyi Hong, Biao Chen:
Quantized consensus ADMM for multi-agent distributed optimization. ICASSP 2016: 4134-4138 - [c6]Shengyu Zhu, Biao Chen:
Distributed detection over connected networks via one-bit quantizer. ISIT 2016: 1526-1530 - [c5]Shengyu Zhu, Biao Chen:
Distributed average consensus with bounded quantization. SPAWC 2016: 1-6 - [i3]Shengyu Zhu, Biao Chen:
Distributed Detection in Ad Hoc Networks Through Quantized Consensus-Part II: Asymptotically Optimal Detection via One-Bit Communications. CoRR abs/1612.01904 (2016) - 2015
- [c4]Shengyu Zhu, Biao Chen:
Distributed average consensus with deterministic quantization: An ADMM approach. GlobalSIP 2015: 692-696 - [i2]Shengyu Zhu, Biao Chen:
Quantized Consensus by the ADMM: Probabilistic versus Deterministic Quantizers. CoRR abs/1502.01053 (2015) - 2014
- [j1]Ge Xu, Shengyu Zhu, Biao Chen:
Decentralized Data Reduction With Quantization Constraints. IEEE Trans. Signal Process. 62(7): 1775-1784 (2014) - 2013
- [c3]Shengyu Zhu, Ge Xu, Biao Chen:
Are global sufficient statistics always sufficient: The impact of quantization on decentralized data reduction. ACSSC 2013: 1090-1094 - [c2]Shengyu Zhu, Biao Chen:
Data reduction in tandem fusion systems. ChinaSIP 2013: 602-606 - [c1]Shengyu Zhu, Earnest Akofor, Biao Chen:
Interactive distributed detection with conditionally independent observations. WCNC 2013: 2531-2535 - [i1]Ge Xu, Shengyu Zhu, Biao Chen:
Decentralized Data Reduction with Quantization Constraints. CoRR abs/1306.1187 (2013)
Coauthor Index
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