Learning representations of ultrahigh-dimensional data for random distance-based outlier detection

• Main Authors: PANG, Guansong, CAO, Longbing, CHEN, Ling, LIAN, Defu, LIU, Huan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Databases and Information Systems; Data Storage Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7141; https://ink.library.smu.edu.sg/context/sis_research/article/8144/viewcontent/11692_Article_Text_15220_1_2_20201228.pdf
• Institution: Singapore Management University

Learning expressive low-dimensional representations of ultrahigh-dimensional data, e.g., data with thousands/millions of features, has been a major way to enable learning methods to address the curse of dimensionality. However, existing unsupervised representation learning methods mainly focus on pr...