A Stabilized Dense Network Approach for High-Dimensional Prediction

Wenjing Yang, Yuhong Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The limitations of traditional statistical methods on high-dimensional gene expression data for inferencing have motivated and expanded research in developing deep learning methods to handle such data more effectively. In this paper, we look into the multi-task learning problem on gene expression inferencing and propose a method that incorporates deep learning techniques and statistical methods and effectively enhances the predictive accuracy in training neural network models for high-dimensional data analysis. Unlike many multi-task learning methods that handle only a relatively small number of tasks, our proposed method demonstrates effective learning capabilities for large-scale tasks up to thousands. In addition, this novel approach is computationally efficient and reproducible, and is capable of producing competitive results with a much simpler network structure in comparison to adversarial methods. The advantages are evident based on the results of the experiments, which are conducted on datasets from the Gene Expression Omnibus and Genotype-Tissue Expression project, both of which provide worldwide range of data resources for gene expression studies and various other data applications.

Original languageEnglish (US)
Title of host publicationIJCNN 2021 - International Joint Conference on Neural Networks, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780738133669
DOIs
StatePublished - Jul 18 2021
Event2021 International Joint Conference on Neural Networks, IJCNN 2021 - Virtual, Shenzhen, China
Duration: Jul 18 2021Jul 22 2021

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2021-July

Conference

Conference2021 International Joint Conference on Neural Networks, IJCNN 2021
Country/TerritoryChina
CityVirtual, Shenzhen
Period7/18/217/22/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • deep learning
  • High-dimensional data
  • stability

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