Search Results for author: Anpeng Wu

Found 8 papers, 5 papers with code

Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series

no code implementations16 Aug 2023 Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu

Learning directed acyclic graphs (DAGs) to identify causal relations underlying observational data is crucial but also poses significant challenges.

Time Series

Instrumental Variables in Causal Inference and Machine Learning: A Survey

1 code implementation12 Dec 2022 Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Fei Wu

This paper serves as the first effort to systematically and comprehensively introduce and discuss the IV methods and their applications in both causal inference and machine learning.

Causal Inference

Confounder Balancing for Instrumental Variable Regression with Latent Variable

no code implementations18 Nov 2022 Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu

This paper studies the confounding effects from the unmeasured confounders and the imbalance of observed confounders in IV regression and aims at unbiased causal effect estimation.


Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation

1 code implementation23 Aug 2022 Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu

The advent of the big data era brought new opportunities and challenges to draw treatment effect in data fusion, that is, a mixed dataset collected from multiple sources (each source with an independent treatment assignment mechanism).


Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI

1 code implementation11 Nov 2021 Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang

However, edge computing, especially edge and cloud collaborative computing, are still in its infancy to announce their success due to the resource-constrained IoT scenarios with very limited algorithms deployed.

Cloud Computing Edge-computing

Treatment effect estimation with confounder balanced instrumental variable regression

no code implementations29 Sep 2021 Anpeng Wu, Kun Kuang, Fei Wu

In this paper, we propose a Confounder Balanced IV Regression (CB-IV) algorithm to jointly remove the bias from the unmeasured confounders with IV regression and reduce the bias from the observed confounders by balancing for treatment effect estimation.


Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition

1 code implementation13 Jul 2021 Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin

We also learn confounder representations by encouraging them to be relevant to both the treatment and the outcome.

Causal Inference

Learning Decomposed Representation for Counterfactual Inference

1 code implementation12 Jun 2020 Anpeng Wu, Kun Kuang, Junkun Yuan, Bo Li, Runze Wu, Qiang Zhu, Yueting Zhuang, Fei Wu

The fundamental problem in treatment effect estimation from observational data is confounder identification and balancing.

Counterfactual Inference

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