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Concept

Weighted least squares

Related publications (29)

On long time behavior of solutions to nonlinear dispersive equations

Stefano Francesco Burzio

In part I, we address the issue of existence of solutions for Cauchy problems involving nonlinear hyperbolic equations for initial data in Sobolev spaces with scaling subcritical regularity. In particular, we analyse nonlinear estimates for null-forms in t ...

EPFL2020

High-Frequency Analysis Of Parabolic Stochastic Pdes

Carsten Hao Ye Chong

We consider the problem of estimating stochastic volatility for a class of second-order parabolic stochastic PDEs. Assuming that the solution is observed at high temporal frequency, we use limit theorems for multipower variations and related functionals to ...

INST MATHEMATICAL STATISTICS2020

Performance Assessment of Kron Reduction in the Numerical Analysis of Polyphase Power Systems

Mario Paolone, Andreas Martin Kettner

This paper investigates the impact of Kron reduction on the performance of numerical methods applied to the analysis of unbalanced polyphase power systems. Specifically, this paper focuses on power-flow study, state estimation, and voltage stability assess ...

IEEE2019

Fitting Markovian binary trees using global and individual demographic data

Sophie Myriam Hautphenne, Katharine Felicity Turner

We consider a class of continuous-time branching processes called Markovian binary trees (MBTs), in which the individuals lifetime and reproduction epochs are modelled using a transient Markovian arrival process (TMAP). We develop methods for estimating th ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Global spatial analysis of toxic emissions to freshwater: operationalization for LCA

Anna Kounina Massé

PurposeThere is increasing interest in using fate and exposure models to spatially differentiate the impacts of chemical emissions. This work aims at exploring the operationalization in life cycle assessment (LCA) of spatially differentiated models for tox ...

SPRINGER HEIDELBERG2019

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

Pascal Frossard, Arun Venkitaraman

In presence of sparse noise we propose kernel regression for predicting output vectors which are smooth over a given graph. Sparse noise models the training outputs being corrupted either with missing samples or large perturbations. The presence of sparse ...

IEEE2019

Numerical Homogenization And Model Order Reduction For Multiscale Inverse Problems

Assyr Abdulle, Andrea Di Blasio

A new numerical method based on numerical homogenization and model order reduction is introduced for the solution of multiscale inverse problems. We consider a class of elliptic problems with highly oscillatory tensors that varies on a microscopic scale. W ...

SIAM PUBLICATIONS2019

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Volkan Cevher, Junhong Lin

We investigate regularized algorithms combining with projection for least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space. We prove convergence results with respect to variants of n ...

ICML2018

Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces

Volkan Cevher, Junhong Lin

In this paper, we study regression problems over a separable Hilbert space with the square loss, covering non-parametric regression over a reproducing kernel Hilbert space. We investigate a class of spectral/regularized algorithms, including ridge regressi ...

2020