no code implementations • 27 Nov 2023 • Xinxing Yang, Genke Yang, Jian Chu
The computational model based on deep learning concatenates the representation of multiple drugs and the corresponding cell line feature as input, and the output is whether the drug combination can have an inhibitory effect on the cell line.
no code implementations • 18 Jul 2023 • Xinxing Yang, Genke Yang, Jian Chu
Moreover, most previous studies tended to design complicated representation learning module, while uniformity, which is used to measure representation quality, is ignored.
no code implementations • 19 May 2023 • Ya-Lin Zhang, Jun Zhou, Yankun Ren, Yue Zhang, Xinxing Yang, Meng Li, Qitao Shi, Longfei Li
In this paper, we consider the problem of long tail scenario modeling with budget limitation, i. e., insufficient human resources for model training stage and limited time and computing resources for model inference stage.
no code implementations • 13 Feb 2023 • Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang
In recommendation scenarios, there are two long-standing challenges, i. e., selection bias and data sparsity, which lead to a significant drop in prediction accuracy for both Click-Through Rate (CTR) and post-click Conversion Rate (CVR) tasks.
no code implementations • 1 Jun 2022 • Xinxing Yang, Genke Yang, Jian Chu
Specifically, we take the drug-disease association prediction problem as the main task, and the auxiliary task is to use data augmentation strategies and contrast learning to mine the internal relationships of the original drug features, so as to automatically learn a better drug representation without supervised labels.
no code implementations • 29 Nov 2021 • Xinxing Yang, Genke Yang, Jian Chu
The limitations of these works are mainly due to the following two reasons: firstly, previous works used negative sampling techniques to treat unvalidated drug-disease associations as negative samples, which is invalid in real-world settings; secondly, the inner product cannot fully take into account the feature information contained in the latent factor of drug and disease.
no code implementations • 16 Sep 2021 • Xinxing Yang, Genke Yangand Jian Chu
We novelly consider the latent factor vector of drugs and diseases as a point in the high-dimensional coordinate system and propose a generalized Euclidean distance to represent the association between drugs and diseases to compensate for the shortcomings of the inner product.
no code implementations • 12 Jun 2020 • Jieyue He, Xinxing Yang, Zhuo Gong, lbrahim Zamit
Then a variant version of the autoencoder is used to extract the latent factor of drugs and diseases to capture the overall information shared by a majority of drug-disease associations.
no code implementations • 5 Mar 2020 • Cen Chen, Chen Liang, Jianbin Lin, Li Wang, Ziqi Liu, Xinxing Yang, Xiukun Wang, Jun Zhou, Yang Shuang, Yuan Qi
The insurance industry has been creating innovative products around the emerging online shopping activities.
no code implementations • 5 Mar 2020 • Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang, Meng Li, Jun Zhou
Machine learning techniques have been widely applied in Internet companies for various tasks, acting as an essential driving force, and feature engineering has been generally recognized as a crucial tache when constructing machine learning systems.
1 code implementation • 27 Feb 2020 • Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song
We present, GEM, the first heterogeneous graph neural network approach for detecting malicious accounts at Alipay, one of the world's leading mobile cashless payment platform.
no code implementations • 18 Jun 2019 • Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan Qi
With the explosive growth of e-commerce and the booming of e-payment, detecting online transaction fraud in real time has become increasingly important to Fintech business.