Image-Based Prognostics Using Penalized Tensor Regression

نویسندگان
چکیده

برای دانلود رایگان 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

Compound identification using penalized linear regression

s Service (CAS) registry number. In the simulation studies, we consider the mass spectra extracted from the NIST Chemistry WebBook (NIST library) as a reference library and the repetitive library as query (experimental) data. In addition, since we assume that the NIST library has the mass spectrum information for all the

متن کامل

Outlier Detection Using Nonconvex Penalized Regression

This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the n data points. We then apply a regularization favoring a sparse vector of mean shift parameters. The usual L1 penalty yields a convex criterion, but we find that it fails to deliver a robust estimator. The L1 penalty corresponds to ...

متن کامل

Sparse Brain Network using Penalized Linear Regression

Sparse partial correlation is a useful connectivity measure for brain networks, especially, when it is hard to compute the exact partial correlation due to the small-n large-p situation. In this paper, we consider a sparse linear regression model with a l1-norm penalty for estimating sparse brain connectivity based on the partial correlation. For the numerical experiments, we construct the spar...

متن کامل

Penalized regression with correlation-based penalty

A new regularization method for regression models is proposed. The criterion to be minimized contains a penalty term which explicitly links strength of penalization to the correlation between predictors. As the elastic net, the method encourages a grouping effect where strongly correlated predictors tend to be in or out of the model together. A boosted version of the penalized estimator, which ...

متن کامل

Nonparametric regression estimation using penalized least squares

We present multivariate penalized least squares regression estimates. We use Vapnik{ Chervonenkis theory and bounds on the covering numbers to analyze convergence of the estimates. We show strong consistency of the truncated versions of the estimates without any conditions on the underlying distribution.

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: Technometrics

سال: 2019

ISSN: 0040-1706,1537-2723

DOI: 10.1080/00401706.2018.1527727