Year: 2017
Type: article
Abstract: We consider the learning algorithms under general source condition with the polynomial decay of the eigenvalues of the integral operator in vector-valued function setting.We discuss the upper convergence rates of Tikhonov regularizer under general source condition corresponding to increasing monotone index function.The convergence issues are studied for general regularization schemes by using the concept of operator monotone index functions in minimax setting.Further we also address the minimum possible error for any learning algorithm.
Authors: Abhishake Rastogi, Sivananthan Sampath
Institutions: University of Genoa, Indian Institute of Technology Delhi
Language: English
Subfield: Mathematical Physics
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,418
OpenAlex ID: W3104466204