Publications related to Polynomial regression

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction a challenging task. Here we propose to use dynamic linear models (DLMs) to a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Fast screening of covariates in population models empowered by machine learning

Jan Sickmann Hesthaven, Nadia Terranova

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervise ...

2021

Sparsest piecewise-linear regression of one-dimensional data

Michaël Unser, Julien René Pierre Fageot, Thomas Jean Debarre, Quentin Alain Denoyelle

We study the problem of one-dimensional regression of data points with total-variation (TV) regularization (in the sense of measures) on the second derivative, which is known to promote piecewise-linear solutions with few knots. While there are efficient a ...

Elsevier2021

A parameter-free mechanistic model of the adhesive wear process of rough surfaces in sliding contact

Jean-François Molinari, Tobias Brink, Lucas Henri Galilée Frérot

In order to develop predictive wear laws, relevant material parameters and their influence on the wear rate need to be identified. Despite decades of research, there is no agreement on the mathematical form of wear equations and even the simplest models, s ...

2021

The association of basic and challenging motor capacity with mobility performance and falls in young seniors

Kamiar Aminian, Anisoara Ionescu

Background: Understanding the association between motor capacity (MC) (what people can do in a standardized environment), mobility performance (MP) (what people actually do in real-life) and falls is important for early detection of and counteracting on fu ...

ELSEVIER IRELAND LTD2020

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Anthony Christopher Davison, Jörg Hager, Hélène Ruffieux

We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, ...

INST MATHEMATICAL STATISTICS2020

Oblivious Sketching of High-Degree Polynomial Kernels

Mikhail Kapralov, Amir Zandieh

Kernel methods are fundamental tools in machine learning that allow detection of non-linear dependencies between data without explicitly constructing feature vectors in high dimensional spaces. A major disadvantage of kernel methods is their poor scalabili ...

ASSOC COMPUTING MACHINERY2020

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou

Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic systolic ...

2020

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Polynomial regression

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Fast screening of covariates in population models empowered by machine learning

Sparsest piecewise-linear regression of one-dimensional data

Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates

Learning Optimal Impedance Control During Complex 3D Arm Movements

A parameter-free mechanistic model of the adhesive wear process of rough surfaces in sliding contact

The association of basic and challenging motor capacity with mobility performance and falls in young seniors

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Oblivious Sketching of High-Degree Polynomial Kernels

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

Graph Chatbot

Chat with Graph Search

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Fast screening of covariates in population models empowered by machine learning

Learning Optimal Impedance Control During Complex 3D Arm Movements

Sparsest piecewise-linear regression of one-dimensional data

The association of basic and challenging motor capacity with mobility performance and falls in young seniors

Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

A parameter-free mechanistic model of the adhesive wear process of rough surfaces in sliding contact

A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression

Oblivious Sketching of High-Degree Polynomial Kernels