7 citations · 13 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 3 cited
MBGDT:Robust Mini-Batch Gradient Descent
Hanming Wang, Haozheng Luo, Yue Wang
In high dimensions, most machine learning method perform fragile even there are a little outliers. To address this, we hope to introduce a new method with the base learner, such as…
stat.ML2021★ 7 cited
Robust factored principal component analysis for matrix-valued outlier accommodation and detection
Xuan Ma, Jianhua Zhao, Yue Wang
Principal component analysis (PCA) is a popular dimension reduction technique for vector data. Factored PCA (FPCA) is a probabilistic extension of PCA for matrix data, which can su…
cs.LG2019★ 3 cited
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation
Zichen Zhang, Qingfeng Lan, Lei Ding +3
Counterfactual reasoning is an important paradigm applicable in many fields, such as healthcare, economics, and education. In this work, we propose a novel method to address the is…