ترجمه مقاله نقش ضروری ارتباطات 6G با چشم انداز صنعت 4.0
- مبلغ: ۸۶,۰۰۰ تومان
ترجمه مقاله پایداری توسعه شهری، تعدیل ساختار صنعتی و کارایی کاربری زمین
- مبلغ: ۹۱,۰۰۰ تومان
Abstract
In this paper, we study and analyze the regularized least squares for functional linear regression model. The approach is to use the reproducing kernel Hilbert space framework and the integral operators. We show with a more general and realistic assumption on the reproducing kernel and input data statistics that the rate of excess prediction risk by the regularized least squares is minimax optimal.
4 Concluding Remarks
In this paper, we have derived the minimax rate of of regularized least squares for functional linear regression. Our required assumptions are more general and realistic than those in the literature. On the other hand, we focus on scalar response in the functional linear model. It would be interesting to consider multiple responses arising from multilinear model and study the corresponding regularized least squares setting as a future research work. Such a setting can have useful applications in image and multi-dimensional signal processing.