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User attribute discovery with missing labels
Cong Y(丛杨); Sun G(孙干); Liu J(刘霁); Yu HB(于海斌); Luo JB(罗杰波)
Source PublicationPattern Recognition
Indexed BySCI ; EI
EI Accession number20173504092595
WOS IDWOS:000412958800003
Contribution Rank1
Funding OrganizationNSFC (61375014, 61533015, U1613214)
KeywordUser Attribute Smart Sensor Multi-task Learning Semi-supervised Learning Missing Labels Low Rank
AbstractIn this paper, we focus on user attribute analysis by recasting such a problem as a multi-task learning issue, where each attribute is considered as an independent task. In comparison with traditional data analysis, the missing labels problem broadly presents for smart sensor data due to some objective / subjective factors, where the label incompleteness increases the difficulty significantly. Therefore, we design a semi-supervised multi-task learning model (S2MTL) to handle the missing labels issue. For modeling, we integrate the matrix factorization to learn the mapping feature dictionary and attribute space information simultaneously, and adopt the pairwise affinity similarity to incorporate the unlabeled data information, where the low rank property and model efficiency can be well controlled. For model optimization, we convert our model as two individual convex subproblems with one non-smooth, and implement an alternating direction method to generate an efficient optimal solution. State-of-the-art models have validated the effectiveness and efficiency of our proposed model via extensive experiments and comparisons, on two public datasets and our new smart building dataset.
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS Research AreaComputer Science ; Engineering
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorCong Y(丛杨)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Department of Computer Science, University of Rochester, Rochester, NY, 14611, United States
Recommended Citation
GB/T 7714
Cong Y,Sun G,Liu J,et al. User attribute discovery with missing labels[J]. Pattern Recognition,2018,73:33-46.
APA Cong Y,Sun G,Liu J,Yu HB,&Luo JB.(2018).User attribute discovery with missing labels.Pattern Recognition,73,33-46.
MLA Cong Y,et al."User attribute discovery with missing labels".Pattern Recognition 73(2018):33-46.
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