Dropout vs. batch normalization: an empirical study of their impact to deep learning von Garbin, Christian, Zhu, Xingquan, Marques, Oge

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Predictive modeling of clinical trial terminations using feature engineering and embedding learning von Elkin, Magdalyn E., Zhu, Xingquan

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Data mining with big data von Wu, Xindong, Zhu, Xingquan, Wu, Gong-Qing, Ding, Wei

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FedDNA: Federated learning using dynamic node alignment von Wang, Shuwen, Zhu, Xingquan

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Deep learning data augmentation for Raman spectroscopy cancer tissue classification von Wu, Man, Wang, Shuwen, Pan, Shirui, Terentis, Andrew C., Strasswimmer, John, Zhu, Xingquan

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Online Feature Selection with Streaming Features von Wu, Xindong, Yu, Kui, Ding, Wei, Wang, Hao, Zhu, Xingquan

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A survey on instance selection for active learning von Fu, Yifan, Zhu, Xingquan, Li, Bin

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Mining With Noise Knowledge: Error-Aware Data Mining von Wu, Xindong, Zhu, Xingquan

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Multi-Instance Learning with Discriminative Bag Mapping von Wu, Jia, Pan, Shirui, Zhu, Xingquan, Zhang, Chengqi, Wu, Xindong

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Computational Data and Social Networks: 12th International Conference, CSoNet 2023, Hanoi, Vietnam, December 11-13, 2023, Proceedings von Hà, Minh Hoàng, Zhu, Xingquan, Thai, My T

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Attributed network embedding via subspace discovery von Zhang, Daokun, Yin, Jie, Zhu, Xingquan, Zhang, Chengqi

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Counting manatee aggregations using deep neural networks and Anisotropic Gaussian Kernel von Wang, Zhiqiang, Pang, Yiran, Ulus, Cihan, Zhu, Xingquan

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Deep Learning for User Interest and Response Prediction in Online Display Advertising von Gharibshah, Zhabiz, Zhu, Xingquan, Hainline, Arthur, Conway, Michael

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Understanding and predicting COVID-19 clinical trial completion vs. cessation von Elkin, Magdalyn E., Zhu, Xingquan

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A survey and taxonomy of adversarial neural networks for text‐to‐image synthesis von Agnese, Jorge, Herrera, Jonathan, Tao, Haicheng, Zhu, Xingquan

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NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints von Wu, Youxi, Tong, Yao, Zhu, Xingquan, Wu, Xindong

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OpenWGL: open-world graph learning for unseen class node classification von Wu, Man, Pan, Shirui, Zhu, Xingquan

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Boosting for Multi-Graph Classification von Wu, Jia, Pan, Shirui, Zhu, Xingquan, Cai, Zhihua

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Bag Constrained Structure Pattern Mining for Multi-Graph Classification von Jia Wu, Xingquan Zhu, Chengqi Zhang, Yu, Philip S.

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CogBoost: Boosting for Fast Cost-Sensitive Graph Classification von Pan, Shirui, Wu, Jia, Zhu, Xingquan

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