Error analysis of kernel regularized pairwise learning with a strongly convex loss
نویسندگان
چکیده
This paper presents a detailed performance analysis for the kernel-based regularized pairwise learning model associated with strongly convex loss. The robustness is analyzed by applying an improved method. results show that has better qualitatively according to probability measure. Some new comparison inequalities are provided, which convergence rates derived. In particular explicit rate obtained in case loss least square
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ژورنال
عنوان ژورنال: Mathematical foundations of computing
سال: 2023
ISSN: ['2577-8838']
DOI: https://doi.org/10.3934/mfc.2022030