Function-on-Function Regression with Mode-Sparsity Regularization

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

compactifications and function spaces on weighted semigruops

chapter one is devoted to a moderate discussion on preliminaries, according to our requirements. chapter two which is based on our work in (24) is devoted introducting weighted semigroups (s, w), and studying some famous function spaces on them, especially the relations between go (s, w) and other function speces are invesigated. in fact this chapter is a complement to (32). one of the main fea...

15 صفحه اول

Feature Selection, Sparsity, Regression Regularization

from Wikipedia A feature selection algorithm can be seen as the combination of a search technique for proposing new feature subsets, along with an evaluation measure which scores the different feature subsets. The simplest algorithm is to test each possible subset of features finding the one which minimizes the error rate. This is an exhaustive search of the space, and is computationally intrac...

متن کامل

Learning a regression function via Tikhonov regularization

We consider the problem of estimating a regression function on the basis of empirical data. We use a Reproducing Kernel Hilbert Space (RKHS) as our hypothesis space, and we follow the methodology of Tikhonov regularization. We show that this leads to a learning scheme that is different from the one usually considered in Learning Theory. Subject to some regularity assumptions on the regression f...

متن کامل

Penalized Function-on-Function Regression

A general framework for smooth regression of a functional response on one or multiple functional predictors is proposed. Using the mixed model representation of penalized regression expands the scope of function-on-function regression to many realistic scenarios. In particular, the approach can accommodate a densely or sparsely sampled functional response as well as multiple functional predicto...

متن کامل

Wavelet Threshold Estimator of Semiparametric Regression Function with Correlated Errors

Wavelet analysis is one of the useful techniques in mathematics which is used much in statistics science recently. In this paper, in addition to introduce the wavelet transformation, the wavelet threshold estimation of semiparametric regression model with correlated errors with having Gaussian distribution is determined and the convergence ratio of estimator computed. To evaluate the wavelet th...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: ACM Transactions on Knowledge Discovery from Data

سال: 2018

ISSN: 1556-4681,1556-472X

DOI: 10.1145/3178113