Exploring uncertainty in pseudo-label guided unsupervised domain adaptation

Jian Liang; Ran He; Zhenan Sun; Tieniu Tan

doi:10.1016/j.patcog.2019.106996

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Exploring uncertainty in pseudo-label guided unsupervised domain adaptation

Jian Liang Ran He Zhenan Sun Tieniu Tan

Year: 2019 Journal: Pattern Recognition Vol: 96 Pages: 106996-106996 Publisher: Elsevier BV

DOI: 10.1016/j.patcog.2019.106996

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Keywords:

Computer science Artificial intelligence Subspace topology Pattern recognition (psychology) Domain (mathematical analysis) Feature (linguistics) Margin (machine learning) Unavailability Class (philosophy) Benchmark (surveying) Machine learning Variance (accounting) Focus (optics) Transformation (genetics) Mathematics Statistics

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Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Machine Learning and ELM

Physical Sciences → Computer Science → Artificial Intelligence

Multimodal Machine Learning Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Exploring uncertainty in pseudo-label guided unsupervised domain adaptation

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