Concept

Multivariate kernel density estimation

Publications associées (56)

Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

SIAM PUBLICATIONS2023

Influence of Fiber Orientation on the Elastic Limit Tensile Stress of UHPFRC

Eugen Brühwiler, Emmanuel Denarié, Jian Zhan

The elastic limit tensile stress of UHPFRC is governed by contributions of the cementitious matrix and the fibrous skeleton. This paper finds that fiber orientation has significant influence on the matrix tensile strength of UHPFRC, while this is not consi ...

2023

Sketches, metrics and fast algorithms

Navid Nouri

As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...

EPFL2022

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Parviz Ghaderi

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation. The trimmed mean of density (TMD), the entropy of dens ...

FRONTIERS MEDIA SA2022

Estimating flexibility preferences to resolve temporal scheduling conflicts in activity-based modelling

Michel Bierlaire, Timothy Michael Hillel, Janody Pougala

This paper presents a novel activity-based demand model that combines an optimisation framework for continuous temporal scheduling decisions (i.e. activity timings and durations) with traditional discrete choice models for non-temporal choice dimensions (i ...

SPRINGER2022

Experimental assessment of traffic density estimation at link and network level with sparse data

Nikolaos Geroliminis, Anna Takayasu

This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitud ...

TAYLOR & FRANCIS LTD2021

Characterization of Microwave Substrates for High Accuracy and Long-Term Stability Using Full-Wave Microstrip Ring Resonator Method

Anja Skrivervik, Yuanyan Su, Miroslav Veljovic

An accurate material characterization method for microwave printed-circuit-board substrates is proposed by combining the microwave ring resonator method with iterative full-wave simulations. A detailed error analysis is performed quantitatively to compensa ...

IEEE2021

Kernel Density Estimation through Density Constrained Near Neighbor Search

Mikhail Kapralov, Navid Nouri

In this paper we revisit the kernel density estimation problem: given a kernel K(x, y) and a dataset of n points in high dimensional Euclidean space, prepare a data structure that can quickly output, given a query q, a (1 + epsilon)-approximation to mu := ...

IEEE2020

Benchmarking of the plane-to-plane metric

Touradj Ebrahimi, Evangelos Alexiou

In this report we benchmark the plane-to-plane objective quality metric. This is, a metric that measures the angular similarity of tangent planes between two point cloud models and relies on normal vectors that are carried with associated pairs of points. ...

2020

A Shared-Memory Parallel Implementation of the RePlAce Global Cell Placer

Mirjana Stojilovic, Philip Brisk, Frédéric Gessler

RePlAce is a state-of-the-art prototype of a flat, analytic, and nonlinear global cell placement algorithm, which models a placement instance as an electrostatic system with positively charged objects. It can handle large-scale standard-cell and mixed-cell ...

IEEE2020

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