کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536209 870482 2015 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A robust semi-supervised learning approach via mixture of label information
ترجمه فارسی عنوان
یک روش قوی یادگیری نیمه نظارت شده از طریق ترکیب اطلاعات برچسب
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی

Due to the fact that limited amounts of labeled data are normally available in real-world, semi-supervised learning has become a popular option, where we expect to use unlabeled data information to improve the learning performance. However, how to use such unlabeled information to make the predicted labels more reliable remains to be a key for any successful learning. In this paper, we propose a semi-supervised learning framework via combination of semi-supervised clustering and semi-supervised classification. In our approach, the predicted labels are selected by both the constrained k-means and safe semi-supervised SVM (S4VMs) to improve the reliability of the predicted labels. Extensive evaluations on collection of benchmarks and real-world action recognition datasets show that the proposed technique outperforms the others.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 68, Part 1, 15 December 2015, Pages 15–21
نویسندگان
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