Concept

Polynomial regression

Related publications (144)

Modeling, Regression and Optimization

This lecture describes the following topics: • Preamble on Linear Algebra • Dynamic and Static Models • Solving Dynamic and Static Models • Solving Regression Problems • Solving Static and Dynamic Optimization Probl ...

2016

Group-Sparse Model Selection: Hardness and Relaxations

Volkan Cevher, Anastasios Kyrillidis, Luca Baldassarre, Nirav Bhan

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these models is the recovery of ``interpretable" signals along with ...

Institute of Electrical and Electronics Engineers2016

Excess-Risk of Distributed Stochastic Learners

Ali H. Sayed

This paper studies the learning ability of consensus and diffusion distributed learners from continuous streams of data arising from different but related statistical distributions. Four distinctive features for diffusion learners are revealed in relation ...

IEEE2016

Predicting Individual Scores From Resting State fMRI Using Partial Least Squares Regression

Dimitri Nestor Alice Van De Ville, Stephan Morgenthaler, Thomas William Arthur Bolton, Maria Giulia Preti, Djalel Eddine Meskaldji

An important question in neuroscience is to reveal the relationship between individual performance and brain activity. This could be achieved by applying model regression techniques, in which functional connectivity derived from resting-state functional ma ...

Ieee2016

On the sensitivity of buildings to climate

Parag Rastogi

Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...

EPFL2016

Predicting transcription factor site occupancy using DNA sequence intrinsic and cell-type specific chromatin features

Philipp Bucher, Sunil Kumar

Background: Understanding the mechanisms by which transcription factors (TF) are recruited to their physiological target sites is crucial for understanding gene regulation. DNA sequence intrinsic features such as predicted binding affinity are often not ve ...

Biomed Central Ltd2016

Definition and assessment of reference values for PMU calibration in static and transient conditions

Mario Paolone, Guglielmo Frigo, Marco Pignati, Daniele Colangelo

The calibration of Phasor Measurement Units (PMUs) consists of comparing Coordinated Universal Time (UTC) time-stamped phasors (synchrophasors) estimated by the PMU under test, against reference synchrophasors generated through a PMU calibrator. The IEEE S ...

IEEE2016

Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery

Roger Gassert, Maria Laura Blefari

Motor imagery (MI) has shown effectiveness in enhancing motor performance. This may be due to the common neural mechanisms underlying MI and motor execution (ME). The main region of the ME network, the primary motor cortex (M1), has been consistently linke ...

Frontiers Research Foundation2015

Process Design and Optimization (MLS-S03): a Journey in Modeling, Optimization and Regression

Julien Léo Billeter

This lecture describes the following topics: • Preamble on Linear Algebra • Dynamic and Static Models • Solving Dynamic and Static Models • Solving Optimization Problems • Solving Regression Problems ...

2015

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

Fabio Nobile, Giovanni Migliorati

Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate functions based on random sampling according to a given probability measure. Recent work has shown that ...

2015

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