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DIWIFT: Discovering Instance-wise Influential Features for Tabular Data.

D. Liu, P. Cheng, H. Zhu, X. Tang, Y. Chen, X. Wang, W. Pan, Z. Ming, и X. He. WWW, стр. 1673-1682. ACM, (2023)

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Cheng-Yung Cheng

Ying Min Cheng

I-Fen Cheng

Xuerong Cheng

Yao Cheng

Другие публикации лиц с тем же именем

Implicit Argument Prediction as Reading Comprehension.P. Cheng, и K. Erk. AAAI, стр. 6284-6291. AAAI Press, (2019)MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection.M. Luo, F. Chen, P. Cheng, Z. Dong, X. He, J. Feng, и Z. Li. WWW, стр. 2507-2513. ACM / IW3C2, (2020)Overcoming Catastrophic Forgetting in Massively Multilingual Continual Learning.G. Winata, L. Xie, K. Radhakrishnan, S. Wu, X. Jin, P. Cheng, M. Kulkarni, и D. Preotiuc-Pietro. ACL (Findings), стр. 768-777. Association for Computational Linguistics, (2023)The UTexas system for TAC SM-KBP task 3: Probabilistic generation of coherent hypotheses.P. Cheng, E. Holgate, и K. Erk. TAC, NIST, (2018)Attending to Entities for Better Text Understanding.P. Cheng, и K. Erk. AAAI, стр. 7554-7561. AAAI Press, (2020)Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset.D. Liu, P. Cheng, Z. Lin, X. Zhang, Z. Dong, R. Zhang, X. He, W. Pan, и Z. Ming. ACM Trans. Inf. Syst., 41 (4): 108:1-108:26 (октября 2023)Mitigating Confounding Bias in Recommendation via Information Bottleneck.D. Liu, P. Cheng, H. Zhu, Z. Dong, X. He, W. Pan, и Z. Ming. RecSys, стр. 351-360. ACM, (2021)A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data.D. Liu, P. Cheng, Z. Dong, X. He, W. Pan, и Z. Ming. SIGIR, стр. 831-840. ACM, (2020)Unsupervised Contrast-Consistent Ranking with Language Models.N. Stoehr, P. Cheng, J. Wang, D. Preotiuc-Pietro, и R. Bhowmik. EACL (1), стр. 900-914. Association for Computational Linguistics, (2024)Counterfactual learning for recommender system.Z. Dong, H. Zhu, P. Cheng, X. Feng, G. Cai, X. He, J. Xu, и J. Wen. RecSys, стр. 568-569. ACM, (2020)

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