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2020 – today
- 2023
[j1]Weijie J. Su, Yuancheng Zhu:
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation. J. Mach. Learn. Res. 24: 124:1-124:53 (2023)- 2020
- [c7]Yihe Wang, Yufei Jin, Yuancheng Zhu, Xiyuan Li, Dazhi Li:
Improved Random Forest Algorithm Based on Attribute Comprehensive Weighting Used in Identification of Missing Data in Power Grid. ICBDS 2020: 599-611
2010 – 2019
- 2018
- [c6]Yuancheng Zhu, John Lafferty:
Distributed Nonparametric Regression under Communication Constraints. ICML 2018: 6004-6012 - [i3]Weijie Su, Yuancheng Zhu:
Statistical Inference for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent. CoRR abs/1802.04876 (2018) - [i2]Yuancheng Zhu, John D. Lafferty:
Distributed Nonparametric Regression under Communication Constraints. CoRR abs/1803.01302 (2018) - 2017
- [c5]Yuancheng Zhu, Zhe Liu, Siqi Sun:
Learning Nonparametric Forest Graphical Models with Prior Information. AISTATS 2017: 672-680 - 2016
- [c4]Sabyasachi Chatterjee, John C. Duchi, John D. Lafferty, Yuancheng Zhu:
Local Minimax Complexity of Stochastic Convex Optimization. NIPS 2016: 3423-3431 - 2015
- [c3]Yuancheng Zhu, Rina Foygel Barber:
The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models. AISTATS 2015 - [i1]Yuancheng Zhu, Zhe Liu, Siqi Sun:
Nonparametric Estimation of Scale-Free Graphical Models. CoRR abs/1511.03796 (2015) - 2014
- [c2]Siqi Sun, Yuancheng Zhu, Jinbo Xu:
Adaptive Variable Clustering in Gaussian Graphical Models. AISTATS 2014: 931-939 - [c1]Yuancheng Zhu, John D. Lafferty:
Quantized Estimation of Gaussian Sequence Models in Euclidean Balls. NIPS 2014: 3662-3670
Coauthor Index
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