کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4616765 | 1339358 | 2013 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Generalization performance of bipartite ranking algorithms with convex losses
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آنالیز ریاضی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Previous works describing the generalization performance of bipartite ranking algorithms are usually based on the assumption of (0–1) loss or the area under the receiver operating characteristic (ROC) curve. In this paper we go far beyond this classical framework by investigating the generalization performance of bipartite ranking algorithms with convex losses over reproducing kernel Hilbert spaces. Based on the McDiarmid inequality and Rademacher complexity, we establish the upper bound on the generalization error for a bipartite ranking algorithm. The theoretical analysis is different from the previous results on error analysis and shows the attractive uniform convergence property of regularized bipartite ranking algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Mathematical Analysis and Applications - Volume 404, Issue 2, 15 August 2013, Pages 528–536
Journal: Journal of Mathematical Analysis and Applications - Volume 404, Issue 2, 15 August 2013, Pages 528–536
نویسندگان
Fangchao He, Hong Chen,