no code implementations • COLING 2022 • Qing Yin, Zhihua Wang, Yunya Song, Yida Xu, Shuai Niu, Liang Bai, Yike Guo, Xian Yang
In this paper, we propose a novel DEC model, which we named the deep embedded clustering model with cluster-level representation learning (DECCRL) to jointly learn cluster and instance level representations.
no code implementations • 21 Feb 2024 • Guandong Li, Xian Yang, Wenpin Ma
Our Ps tamper detection method includes three steps: feature assistance, audit point positioning, and tamper recognition.
no code implementations • 28 Dec 2023 • Guandong Li, Xian Yang
This framework comprises material recognition, preprocess, smartname, and label layers.
1 code implementation • 18 Jan 2022 • Shuai Niu, Yunya Song, Qing Yin, Yike Guo, Xian Yang
Thirdly, both label-dependent and event-guided representations are integrated to make a robust prediction, in which the interpretability is enabled by the attention weights over words from medical notes.
1 code implementation • 18 Jan 2022 • Shuai Niu, Qing Yin, Yunya Song, Yike Guo, Xian Yang
In this paper, we propose a label dependent attention model LDAM to 1) improve the interpretability by exploiting Clinical-BERT (a biomedical language model pre-trained on a large clinical corpus) to encode biomedically meaningful features and labels jointly; 2) extend the idea of joint embedding to the processing of time-series data, and develop a multi-modal learning framework for integrating heterogeneous information from medical notes and time-series health status indicators.
no code implementations • EMNLP 2021 • Jingqing Zhang, Luis Bolanos, Tong Li, Ashwani Tanwar, Guilherme Freire, Xian Yang, Julia Ive, Vibhor Gupta, Yike Guo
Contextualised word embeddings is a powerful tool to detect contextual synonyms.
no code implementations • 28 Oct 2020 • Chen Wu, Xian Yang, Sencun Zhu, Prasenjit Mitra
To minimize the pruning influence on test accuracy, we can fine-tune after pruning, and the attack success rate drops to 6. 4%, with only a 1. 7% loss of test accuracy.
1 code implementation • 25 Apr 2020 • Philip Nadler, Shuo Wang, Rossella Arcucci, Xian Yang, Yike Guo
We compare and discuss model results which conducts updates as new observations become available.
1 code implementation • 10 Nov 2019 • Jingqing Zhang, Xiao-Yu Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo
The extraction of phenotype information which is naturally contained in electronic health records (EHRs) has been found to be useful in various clinical informatics applications such as disease diagnosis.
4 code implementations • 17 Aug 2019 • Xiao-Yu Zhang, Jingqing Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo
The training procedure of OmiVAE is comprised of an unsupervised phase without the classifier and a supervised phase with the classifier.