Counterfactual learning for recommender system. - Zhenhua Dong; Hong Zhu 003; Pengxiang Cheng 002; Xinhua Feng; Guohao Cai; Xiuqiang He 001; Jun Xu 001; Jirong Wen (RecSys, 2020)

A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data. - Dugang Liu; Pengxiang Cheng 002; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (SIGIR, 2020)

MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection. - Mi Luo; Fei Chen 013; Pengxiang Cheng 002; Zhenhua Dong; Xiuqiang He 001; Jiashi Feng; Zhenguo Li (WWW, 2020)

Mitigating Confounding Bias in Recommendation via Information Bottleneck. - Dugang Liu; Pengxiang Cheng 002; Hong Zhu 003; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (RecSys, 2021)

DIWIFT: Discovering Instance-wise Influential Features for Tabular Data. - Dugang Liu; Pengxiang Cheng 002; Hong Zhu 003; Xing Tang 007; Yanyu Chen; Xiaoting Wang; Weike Pan; Zhong Ming 001; Xiuqiang He 001 (WWW, 2023)

Debiased Representation Learning in Recommendation via Information Bottleneck. - Dugang Liu; Pengxiang Cheng 002; Hong Zhu 003; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (Trans. Recomm. Syst., 2023)

KDCRec: Knowledge Distillation for Counterfactual Recommendation via Uniform Data. - Dugang Liu; Pengxiang Cheng 002; Zinan Lin 004; Jinwei Luo; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (IEEE Trans. Knowl. Data Eng., 2023)

Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset. - Dugang Liu; Pengxiang Cheng 002; Zinan Lin 004; Xiaolian Zhang; Zhenhua Dong; Rui Zhang 003; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (ACM Trans. Inf. Syst., 2023)