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2020 – today
- 2024
[c12]Junpeng Fang, Gongduo Zhang, Qing Cui, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou:
Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations. AAAI 2024: 11944-11952- [c11]Dong Yao
, Caizhi Tang, Qing Cui, Longfei Li:
Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects. CIKM 2024: 2961-2970 - [c10]Ya-Lin Zhang, Caizhi Tang, Lu Yu, Jun Zhou, Longfei Li, Qing Cui, Fangfang Fan, Linbo Jiang, Xiaosong Zhao:
Domain Level Interpretability: Interpreting Black-box Model with Domain-specific Embedding. WSDM 2024: 1102-1105 - [c9]Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang:
Invariant Graph Learning for Causal Effect Estimation. WWW 2024: 2552-2562 - [i1]Dong Yao, Caizhi Tang, Qing Cui, Longfei Li:
Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects. CoRR abs/2410.21343 (2024) - 2023
- [j2]Caizhi Tang, Qing Cui, Longfei Li, Jun Zhou:
GINT: A Generative Interpretability method via perturbation in the latent space. Expert Syst. Appl. 232: 120570 (2023) - [c8]Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Longfei Li, Jun Zhou:
Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. ICML 2023: 33792-33803 - [c7]Jia Gu, Caizhi Tang, Han Yan, Qing Cui, Longfei Li, Jun Zhou:
FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation. NeurIPS 2023 - [c6]Junpeng Fang, Qing Cui, Gongduo Zhang, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou, Fei Wu:
Alleviating Matching Bias in Marketing Recommendations. SIGIR 2023: 3359-3363 - [c5]Jun Zhou, Caizhi Tang, Qing Cui, Yi Ding, Longfei Li, Fei Wu:
DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay. WWW (Companion Volume) 2023: 447-451 - 2022
- [j1]Jun-Peng Fang, Jun Zhou, Qing Cui, Caizhi Tang, Longfei Li:
Interpreting Model Predictions with Constrained Perturbation and Counterfactual Instances. Int. J. Pattern Recognit. Artif. Intell. 36(1): 2251001:1-2251001:23 (2022) - [c4]Jun-Peng Fang, Caizhi Tang, Qing Cui, Feng Zhu, Longfei Li, Jun Zhou, Wei Zhu:
Semi-Supervised Learning with Data Augmentation for Tabular Data. CIKM 2022: 3928-3932 - [c3]Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Ya-Lin Zhang, Feng Zhu, Longfei Li, Jun Zhou, Linbo Jiang:
Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. NeurIPS 2022 - 2020
- [c2]Qing Cui, Qitao Shi, Hao Qian, Caizhi Tang, Xixi Li, Yiming Zhao, Tao Jiang, Longfei Li, Jun Zhou:
AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models. ECML/PKDD (5) 2020: 541-545
2010 – 2019
- 2019
- [c1]Cen Chen, Xiaolu Zhang, Sheng Ju, Chilin Fu, Caizhi Tang, Jun Zhou, Xiaolong Li:
AntProphet: an Intention Mining System behind Alipay's Intelligent Customer Service Bot. IJCAI 2019: 6497-6499
Coauthor Index
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