Search Results for author: Xian Yang

Found 10 papers, 5 papers with code

Improving Deep Embedded Clustering via Learning Cluster-level Representations

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.

Clustering Contrastive Learning +2

A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition

no code implementations21 Feb 2024 Guandong Li, Xian Yang, Wenpin Ma

Our Ps tamper detection method includes three steps: feature assistance, audit point positioning, and tamper recognition.

Dimensionality Reduction Retrieval

Label-dependent and event-guided interpretable disease risk prediction using EHRs

1 code implementation18 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.

Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records

1 code implementation18 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.

Language Modelling Time Series +1

Mitigating Backdoor Attacks in Federated Learning

no code implementations28 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.

Federated Learning

An Epidemiological Modelling Approach for Covid19 via Data Assimilation

1 code implementation25 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.

Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records

1 code implementation10 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.

Computational Efficiency

Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification

4 code implementations17 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.

Classification Decision Making +3

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