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2020 – today
- 2024
[c7]Yixuan Zhang, Boyu Li, Zenan Ling, Feng Zhou:
Mitigating Label Bias in Machine Learning: Fairness through Confident Learning. AAAI 2024: 16917-16925- [c6]Huiying Yang, Rujing Xiong, Yao Xiao, Zhijie Fan, Tiebin Mi, Robert Caiming Qiu, Zenan Ling:
Codebook Configuration for RIS-Aided Systems via Implicit Neural Representations. ICC 2024: 1449-1454 - [c5]Zenan Ling, Longbo Li, Zhanbo Feng, Yixuan Zhang, Feng Zhou, Robert C. Qiu, Zhenyu Liao:
Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures. ICML 2024 - [i13]Zenan Ling, Longbo Li, Zhanbo Feng, Yixuan Zhang, Feng Zhou, Robert C. Qiu, Zhenyu Liao:
Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures. CoRR abs/2402.02697 (2024) - [i12]Huiying Yang, Zihan Jin, Chenhao Wu, Rujing Xiong, Robert Caiming Qiu, Zenan Ling:
R-NeRF: Neural Radiance Fields for Modeling RIS-enabled Wireless Environments. CoRR abs/2405.11541 (2024) - 2023
- [j8]Xingyu Xie
, Qiuhao Wang, Zenan Ling, Xia Li, Guangcan Liu, Zhouchen Lin:
Optimization Induced Equilibrium Networks: An Explicit Optimization Perspective for Understanding Equilibrium Models. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3604-3616 (2023) - [c4]Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin:
Global Convergence of Over-parameterized Deep Equilibrium Models. AISTATS 2023: 767-787 - [c3]Zongpeng Zhang, Zenan Ling, Tong Lin, Zhouchen Lin:
Gradient Descent Optimizes Normalization-Free ResNets. IJCNN 2023: 1-8 - [c2]Tianjun Ke, Haoqun Cao, Zenan Ling, Feng Zhou:
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification. NeurIPS 2023 - [i11]Yao Xiao, Zhijie Fan, Zenan Ling, Rujing Xiong, Tiebin Mi, Robert Caiming Qiu:
Codebook Configuration for 1-bit RIS-aided Systems Based on Implicit Neural Representations. CoRR abs/2306.00544 (2023) - [i10]Zhanbo Feng, Zenan Ling, Ci Gong, Feng Zhou, Jie Li, Robert C. Qiu:
Zero-shot Inversion Process for Image Attribute Editing with Diffusion Models. CoRR abs/2308.15854 (2023) - [i9]Zenan Ling, Zhenyu Liao, Robert C. Qiu:
On the Equivalence between Implicit and Explicit Neural Networks: A High-dimensional Viewpoint. CoRR abs/2308.16425 (2023) - [i8]Tianjun Ke, Haoqun Cao, Zenan Ling, Feng Zhou:
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification. CoRR abs/2310.10379 (2023) - [i7]Yixuan Zhang, Boyu Li, Zenan Ling, Feng Zhou:
Mitigating Label Bias in Machine Learning: Fairness through Confident Learning. CoRR abs/2312.08749 (2023) - 2022
- [c1]Zenan Ling, Fan Zhou, Meng Wei, Quanshi Zhang:
Exploring Image Regions Not Well Encoded by an INN. AISTATS 2022: 483-509 - [i6]Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin:
Global Convergence of Over-parameterized Deep Equilibrium Models. CoRR abs/2205.13814 (2022) - 2021
- [j7]Zenan Ling, Robert C. Qiu, Xing He, Lei Chu:
A New Approach of Exploiting Self-Adjoint Matrix Polynomials of Large Random Matrices for Anomaly Detection and Fault Location. IEEE Trans. Big Data 7(3): 548-558 (2021) - [j6]Fan Yang, Mingjie Wei, Zenan Ling, Tiebin Mi, Haosen Yang, Robert C. Qiu:
Brown Measure Based Spectral Distribution Analysis for Spatial-Temporal Localization of Cascading Events in Power Grids. IEEE Trans. Smart Grid 12(2): 1805-1820 (2021) - [i5]Xingyu Xie, Qiuhao Wang, Zenan Ling, Xia Li, Yisen Wang, Guangcan Liu, Zhouchen Lin:
Optimization Induced Equilibrium Networks. CoRR abs/2105.13228 (2021) - 2020
- [j5]Xin Shi, Robert C. Qiu, Zenan Ling, Fan Yang, Haosen Yang, Xing He:
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks. IEEE Trans. Smart Grid 11(2): 995-1006 (2020)
2010 – 2019
- 2019
- [j4]Zenan Ling, Robert C. Qiu:
Spectrum Concentration in Deep Residual Learning: A Free Probability Approach. IEEE Access 7: 105212-105223 (2019) - [i4]Zenan Ling, Haotian Ma, Yu Yang, Robert C. Qiu, Song-Chun Zhu, Quanshi Zhang:
Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks. CoRR abs/1901.02184 (2019) - 2018
- [j3]Xing He, Lei Chu, Robert Caiming Qiu, Qian Ai, Zenan Ling:
A Novel Data-Driven Situation Awareness Approach for Future Grids - Using Large Random Matrices for Big Data Modeling. IEEE Access 6: 13855-13865 (2018) - [j2]Lei Chu, Robert C. Qiu, Xing He, Zenan Ling, Yadong Liu:
Massive Streaming PMU Data Modelling and Analytics in Smart Grid State Evaluation based on Multiple High-Dimensional Covariance Test. IEEE Trans. Big Data 4(1): 55-64 (2018) - [i3]Zenan Ling, Robert C. Qiu, Zhijian Jin, Yuhang Zhang, Xing He, Haichun Liu, Lei Chu:
An Accurate and Real-time Self-blast Glass Insulator Location Method Based On Faster R-CNN and U-net with Aerial Images. CoRR abs/1801.05143 (2018) - [i2]Zenan Ling, Robert C. Qiu:
Spectrum concentration in deep residual learning: a free probability appproach. CoRR abs/1807.11694 (2018) - 2017
- [i1]Lei Chu, Robert C. Qiu, Haichun Liu, Zenan Ling, Xin Shi:
Individual Recognition in Schizophrenia using Deep Learning Methods with Random Forest and Voting Classifiers: Insights from Resting State EEG Streams. CoRR abs/1707.03467 (2017) - 2016
- [j1]Xing He, Robert Caiming Qiu, Qian Ai, Lei Chu, Xinyi Xu, Zenan Ling:
Designing for Situation Awareness of Future Power Grids: An Indicator System Based on Linear Eigenvalue Statistics of Large Random Matrices. IEEE Access 4: 3557-3568 (2016)
Coauthor Index
aka: Robert Caiming Qiu
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