Learning from Proportions of Positive and Unlabeled Examples-Reference-Cited by-同舟云学术

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Learning from Proportions of Positive and Unlabeled Examples

Published:2016-07-09 Issue:2 Volume:32 Page:109-133
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int. J. Intell. Syst.

Author:

Hernández-González Jerónimo¹,Inza Iñaki¹,Lozano José A.¹²

Affiliation:

1. Intelligent Systems Group; University of the Basque Country UPV/EHU; 20018 Donostia Spain

2. Basque Center for Applied Mathematics BCAM; 48009 Bilbao Spain

Funder

Eusko Jaurlaritza

Spanish Ministry of Economy and Competitiveness

Basque Government and University of the Basque Country UPV/EHU

Publisher

Wiley

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Reference39 articles.

1. Weak supervision and other non-standard classification problems: a taxonomy;Hernández-González;Pattern Recognit Lett,2016

2. Semi-Supervised Learning

3. Introduction to semi-supervised learning;Zhu;Synth Lect Artif Intell Mach Learn,2009

4. Wrapper positive Bayesian network classifiers;Calvo;Knowl Inform Syst,2012

5. Learning Bayesian network classifiers from label proportions;Hernández-González;Pattern Recognit,2013

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Positive Unlabeled Learning;Synthesis Lectures on Artificial Intelligence and Machine Learning;2022-04-19

2. Robust KPI Anomaly Detection for Large-Scale Software Services with Partial Labels;2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE);2021-10

3. Dissecting click farming on the Taobao platform in China via PU learning and weighted logistic regression;Electronic Commerce Research;2020-06-02

4. Positive unlabeled learning for building recommender systems in a parliamentary setting;Information Sciences;2018-04

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