Results 11 to 20 of about 4,421,578 (317)
SIAM Journal on Optimization, 2023 Convex regression is the problem of fitting a convex function to a data set consisting of input-output pairs. We present a new approach to this problem called spectrahedral regression, in which we fit a spectrahedral function to the data, i.e. a function that is the maximum eigenvalue of an affine matrix expression of the input.
Eliza O'Reilly, Venkat Chandrasekaran
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Collaborative regression [PDF]
Biostatistics, 2014 13 pages, 4 ...
Gross, Samuel M., Tibshirani, Robert
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Foundations and Trends® in Machine Learning, 2021 The presence of multidirectional correlations in emerging multidimensional data poses a challenge to traditional regression modeling methods. Traditional modeling methods based on matrix or vector, for example, not only overlook the data’s multidimensional information and lower model performance, but also add additional computations and storage ...
Jiani Liu 0002 +3 more
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Logistic regression diagnostics in ridge regression
Computational Statistics, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Revan Özkale +2 more
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Machine Learning, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Journal of Multivariate Analysis, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alexis Derumigny, Jean-David Fermanian
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Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020 This paper introduces a novel Robust Regression (RR) model, named Sinkhorn regression, which imposes Sinkhorn distances on both loss function and regularization. Traditional RR methods target at searching for an element-wise loss function (e.g., Lp-norm) to characterize the errors such that outlying data have a relatively smaller influence on ...
Lei Luo 0001 +2 more
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Continuum Regression and Ridge Regression
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1993 SUMMARY We demonstrate the close relationship between first-factor continuum regression and standard ridge regression. The difference is that continuum regression inserts a scalar compensation factor for that part of the shrinkage in ridge regression that has no connection with tendencies towards collinearity.
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background 131I‐metaiodobenzylguanidine (131I‐MIBG) radiotherapy is a key treatment for relapsed and refractory (R/R) neuroblastoma (NB). Patients with R/R disease treated in the modern era are increasingly exposed to anti‐GD2 immunotherapy, which exerts selective pressure and may modify both tumor cell state and microenvironment.
Benjamin J. Lerman +7 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
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