Multi-view Semi-supervised Learning Using Privileged Information

Evgueni Smirnov; Richard Delava; Ron Diris; Nikolay Nikolaev

doi:10.1007/978-3-031-34204-2_13

Multi-view Semi-supervised Learning Using Privileged Information

Evgueni Smirnov^*, Richard Delava, Ron Diris, Nikolay Nikolaev

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

In this paper we propose to combine the paradigm of multi-view semi-supervised learning with that of learning using privileged information. The combination is realized by a new method that we introduce in detail. A distinctive feature of the method is that it is classifier agnostic which contracts with most of the methods for learning using privileged information. An experimental study on a real-life problem shows that using privileged information is capable of improving multi-view semi-supervised learning.

Original language	English
Title of host publication	Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings
Editors	Lazaros Iliadis, Ilias Maglogiannis, Serafin Alonso, Chrisina Jayne, Elias Pimenidis
Publisher	Springer
Pages	144-152
Number of pages	9
Volume	1826 CCIS
ISBN (Print)	9783031342035
DOIs	https://doi.org/10.1007/978-3-031-34204-2_13
Publication status	Published - 1 Jan 2023
Event	24th International Conference on Engineering Applications of Neural Networks - León, Spain Duration: 14 Jun 2023 → 17 Jun 2023 Conference number: 24 https://eannconf.org/2023/

Publication series

Series	Communications in Computer and Information Science
Volume	1826 CCIS
ISSN	1865-0929

Conference

Conference	24th International Conference on Engineering Applications of Neural Networks
Abbreviated title	EANN / EAAAI 2023
Country/Territory	Spain
City	León
Period	14/06/23 → 17/06/23
Internet address	https://eannconf.org/2023/

Access to Document

10.1007/978-3-031-34204-2_13

Cite this

Smirnov, E., Delava, R., Diris, R., & Nikolaev, N. (2023). Multi-view Semi-supervised Learning Using Privileged Information. In L. Iliadis, I. Maglogiannis, S. Alonso, C. Jayne, & E. Pimenidis (Eds.), Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings (Vol. 1826 CCIS, pp. 144-152). Springer. https://doi.org/10.1007/978-3-031-34204-2_13

Smirnov, Evgueni ; Delava, Richard ; Diris, Ron et al. / Multi-view Semi-supervised Learning Using Privileged Information. Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings. editor / Lazaros Iliadis ; Ilias Maglogiannis ; Serafin Alonso ; Chrisina Jayne ; Elias Pimenidis. Vol. 1826 CCIS Springer, 2023. pp. 144-152 (Communications in Computer and Information Science, Vol. 1826 CCIS).

@inbook{6115f02669d8462381bce0ba557186b2,

title = "Multi-view Semi-supervised Learning Using Privileged Information",

abstract = "In this paper we propose to combine the paradigm of multi-view semi-supervised learning with that of learning using privileged information. The combination is realized by a new method that we introduce in detail. A distinctive feature of the method is that it is classifier agnostic which contracts with most of the methods for learning using privileged information. An experimental study on a real-life problem shows that using privileged information is capable of improving multi-view semi-supervised learning.",

author = "Evgueni Smirnov and Richard Delava and Ron Diris and Nikolay Nikolaev",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 24th International Conference on Engineering Applications of Neural Networks, EANN / EAAAI 2023 ; Conference date: 14-06-2023 Through 17-06-2023",

year = "2023",

month = jan,

day = "1",

doi = "10.1007/978-3-031-34204-2_13",

language = "English",

isbn = "9783031342035",

volume = "1826 CCIS",

series = "Communications in Computer and Information Science",

publisher = "Springer",

pages = "144--152",

editor = "Lazaros Iliadis and Ilias Maglogiannis and Serafin Alonso and Chrisina Jayne and Elias Pimenidis",

booktitle = "Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings",

address = "United States",

url = "https://eannconf.org/2023/",

}

Smirnov, E, Delava, R, Diris, R & Nikolaev, N 2023, Multi-view Semi-supervised Learning Using Privileged Information. in L Iliadis, I Maglogiannis, S Alonso, C Jayne & E Pimenidis (eds), Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings. vol. 1826 CCIS, Springer, Communications in Computer and Information Science, vol. 1826 CCIS, pp. 144-152, 24th International Conference on Engineering Applications of Neural Networks, León, Spain, 14/06/23. https://doi.org/10.1007/978-3-031-34204-2_13

Multi-view Semi-supervised Learning Using Privileged Information. / Smirnov, Evgueni; Delava, Richard; Diris, Ron et al.
Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings. ed. / Lazaros Iliadis; Ilias Maglogiannis; Serafin Alonso; Chrisina Jayne; Elias Pimenidis. Vol. 1826 CCIS Springer, 2023. p. 144-152 (Communications in Computer and Information Science, Vol. 1826 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

TY - CHAP

T1 - Multi-view Semi-supervised Learning Using Privileged Information

AU - Smirnov, Evgueni

AU - Delava, Richard

AU - Diris, Ron

AU - Nikolaev, Nikolay

N1 - Conference code: 24

PY - 2023/1/1

Y1 - 2023/1/1

N2 - In this paper we propose to combine the paradigm of multi-view semi-supervised learning with that of learning using privileged information. The combination is realized by a new method that we introduce in detail. A distinctive feature of the method is that it is classifier agnostic which contracts with most of the methods for learning using privileged information. An experimental study on a real-life problem shows that using privileged information is capable of improving multi-view semi-supervised learning.

AB - In this paper we propose to combine the paradigm of multi-view semi-supervised learning with that of learning using privileged information. The combination is realized by a new method that we introduce in detail. A distinctive feature of the method is that it is classifier agnostic which contracts with most of the methods for learning using privileged information. An experimental study on a real-life problem shows that using privileged information is capable of improving multi-view semi-supervised learning.

UR - http://www.scopus.com/inward/record.url?scp=85163949548&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-34204-2_13

DO - 10.1007/978-3-031-34204-2_13

M3 - Chapter

SN - 9783031342035

VL - 1826 CCIS

T3 - Communications in Computer and Information Science

SP - 144

EP - 152

BT - Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings

A2 - Iliadis, Lazaros

A2 - Maglogiannis, Ilias

A2 - Alonso, Serafin

A2 - Jayne, Chrisina

A2 - Pimenidis, Elias

PB - Springer

T2 - 24th International Conference on Engineering Applications of Neural Networks

Y2 - 14 June 2023 through 17 June 2023

ER -

Smirnov E, Delava R, Diris R, Nikolaev N. Multi-view Semi-supervised Learning Using Privileged Information. In Iliadis L, Maglogiannis I, Alonso S, Jayne C, Pimenidis E, editors, Engineering Applications of Neural Networks - 24th International Conference, EAAAI/EANN 2023, Proceedings. Vol. 1826 CCIS. Springer. 2023. p. 144-152. (Communications in Computer and Information Science, Vol. 1826 CCIS). doi: 10.1007/978-3-031-34204-2_13

Multi-view Semi-supervised Learning Using Privileged Information

Abstract

Publication series

Conference

Access to Document

Other files and links

Cite this