Positive unlabeled learning with tensor networks

Žunkovič, Bojan (author)

Positive unlabeled learning is a binary classification problem with positive and unlabeled data. It is common in domains where negative labels are costly or impossible to obtain, e.g., medicine and personalized advertising. Most approaches to positive unlabeled learning apply to specific data types (e.g., images, categorical data) and can not generate new positive and negative samples. This work introduces a feature-space distance-based tensor network approach to the positive unlabeled learning problem. The presented method is not domain specific and significantly improves the state-of-the-art results on the MNIST image and 15 categorical/mixed datasets. The trained tensor network model is also a generative model and enables the generation of new positive and negative instances.

• Language: English
• Keywords: positive unlabeled learning, tensor networks, matrix product states
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2023
• Number of pages: 11 str.
• Numbering: Vol. 552, art. 126556
• PID: 20.500.12556/RUL-153064
• UDC: 004
• ISSN on article: 0925-2312
• DOI: 10.1016/j.neucom.2023.126556
• COBISS.SI-ID: 177078019
• Publication date in RUL: 15.12.2023

Record is a part of a journal

• Title: Neurocomputing
• Shortened title: Neurocomputing
• Publisher: Elsevier
• ISSN: 0925-2312
• COBISS.SI-ID: 172315

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: pozitivno neoznačeno učenje, tenzorske mreže, matrično produktni nastavek

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: J1-2480
• Name: Tenzorske mreže kot povezava med klasičnim in kvantnim strojnim učenjem