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Scalable Nonparametric L1 Density Estimation via Sparse Subtree Partitioning

Master-uppsats

Sandstedt, Axel

Uppsala universitet/Statistik, AI och data science

Publicerad: 2023

Språk: Engelska

Nyckelord

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⌕Anomaly Detection⌕Regression analysis⌕L1⌕density estimation⌕scalable density estimation⌕nonparametric density estimation⌕scalable nonparametric density estimation⌕L_1

Sammanfattning

We consider the construction of multivariate histogram estimators for any density f seeking to minimize its L1 distance to the true underlying density using arbitrarily large sample sizes. Theory for such estimators exist and the early stages of distributed implementations are available. Our main contributions are new algorithms which seek to optimise out unnecessary network communication taking place in the distributed stages of the construction of such estimators using sparse binary tree arithmetics.

Information

Författare
Sandstedt, Axel
Lärosäte / institution
Uppsala universitet/Statistik, AI och data science
Publiceringsdatum
2023
Uppsatstyp
Master-uppsats
Språk
Engelska
Nyckelord
⌕Anomaly Detection⌕Regression analysis⌕L1⌕density estimation⌕scalable density estimation⌕nonparametric density estimation⌕scalable nonparametric density estimation⌕L_1

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