On a Weakly Supervised Classification Problem

Vladimir Berikov, Alexander Litvinenko, Igor Pestunov, Yuriy Sinyavskiy

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review


We consider a weakly supervised classification problem. It is a classification problem where the target variable can be unknown or uncertain for some subset of samples. This problem appears when the labeling is impossible, time-consuming, or expensive. Noisy measurements and lack of data may prevent accurate labeling. Our task is to build an optimal classification function. For this, we construct and minimize a specific objective function, which includes the fitting error on labeled data and a smoothness term. Next, we use covariance and radial basis functions to define the degree of similarity between points. The further process involves the repeated solution of an extensive linear system with the graph Laplacian operator. To speed up this solution process, we introduce low-rank approximation techniques. We call the resulting algorithm WSC-LR. Then we use the WSC-LR algorithm for analysis CT brain scans to recognize ischemic stroke disease. We also compare WSC-LR with other well-known machine learning algorithms.

Original languageEnglish
Title of host publicationAnalysis of Images, Social Networks and Texts - 10th International Conference, AIST 2021, Revised Selected Papers
EditorsEvgeny Burnaev, Sergei Ivanov, Alexander Panchenko, Dmitry I. Ignatov, Sergei O. Kuznetsov, Michael Khachay, Olessia Koltsova, Andrei Kutuzov, Natalia Loukachevitch, Amedeo Napoli, Panos M. Pardalos, Jari Saramäki, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages15
ISBN (Print)9783031164996
Publication statusPublished - 2022
Event10th International Conference on Analysis of Images, Social Networks and Texts, AIST 2021 - Tbilisi, Georgia
Duration: 16 Dec 202118 Dec 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13217 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Conference on Analysis of Images, Social Networks and Texts, AIST 2021


  • Computed tomography
  • Low-rank approximation
  • Manifold regularization
  • Similarity matrix
  • Uncertainty model
  • Weakly supervised classification




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