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Ruocheng Guo
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Publications
- 2023
- [j11]Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, Kasim Selçuk Candan:
Causal Disentanglement for Implicit Recommendations with Network Information. ACM Trans. Knowl. Discov. Data 17(7): 94:1-94:18 (2023) - 2022
- [j9]Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu:
Evaluation Methods and Measures for Causal Learning Algorithms. IEEE Trans. Artif. Intell. 3(6): 924-943 (2022) - [c36]Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu:
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. ICWSM 2022: 67-78 - [c32]Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selçuk Candan, Huan Liu:
Causal Disentanglement with Network Information for Debiased Recommendations. SISAP 2022: 265-273 - [i32]Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu:
Evaluation Methods and Measures for Causal Learning Algorithms. CoRR abs/2202.02896 (2022) - [i30]Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, K. Selçuk Candan:
Causal Disentanglement with Network Information for Debiased Recommendations. CoRR abs/2204.07221 (2022) - 2021
- [c27]Paras Sheth, Ujun Jeong, Ruocheng Guo, Huan Liu, K. Selçuk Candan:
CauseBox: A Causal Inference Toolbox for BenchmarkingTreatment Effect Estimators with Machine Learning Methods. CIKM 2021: 4789-4793 - [i22]Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu:
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. CoRR abs/2110.01746 (2021) - 2020
- [c22]Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data. IJCAI 2020: 4534-4540 - [c19]Lu Cheng, Ruocheng Guo, K. Selçuk Candan, Huan Liu:
Representation Learning for Imbalanced Cross-Domain Classification. SDM 2020: 478-486 - 2019
- [c14]Lu Cheng, Ruocheng Guo, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
A Practical Data Repository for Causal Learning with Big Data. Bench 2019: 234-248
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