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pro vyhledávání: '"Pham, Nhat Thien"'
Autor:
Chamroukhi, Faïcel, Pham, Nhat Thien
In modern machine learning problems we deal with datasets that are either distributed by nature or potentially large for which distributing the computations is usually a standard way to proceed, since centralized algorithms are in general ineffective
Externí odkaz:
http://arxiv.org/abs/2312.09877
Autor:
Pham, Nhat Thien, Chamroukhi, Faicel
We develop a mixtures-of-experts (ME) approach to the multiclass classification where the predictors are univariate functions. It consists of a ME model in which both the gating network and the experts network are constructed upon multinomial logisti
Externí odkaz:
http://arxiv.org/abs/2202.13934
We consider the statistical analysis of heterogeneous data for prediction in situations where the observations include functions, typically time series. We extend the modeling with Mixtures-of-Experts (ME), as a framework of choice in modeling hetero
Externí odkaz:
http://arxiv.org/abs/2202.02249
Autor:
Le, Thanh-Hieu, Pham, Nhat-Thien
The paper proves sum-of-square-of-rational-function based representations (shortly, sosrf-based representations) of polynomial matrices that are positive semidefinite on some special sets: $\mathbb{R}^n;$ $\mathbb{R}$ and its intervals $[a,b]$, $[0,\
Externí odkaz:
http://arxiv.org/abs/1901.02360
Akademický článek
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We consider the statistical analysis of heterogeneous data for clustering and prediction purposes, in situations where the observations include functions, typically time series. We extend the modeling with Mixtures-of-Experts (ME), as a framework of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a15dfa71ba88034e1e28b813386dbf9e
http://arxiv.org/abs/2202.02249
http://arxiv.org/abs/2202.02249
Dual-energy computed tomography (DECT) is an advanced CT scanning technique enabling material characterization not possible with conventional CT scans. It allows the reconstruction of energy decay curves at each 3D image voxel, representing varying i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d07943ee47808fe5f6eb5edaeb23fe9
https://doi.org/10.36227/techrxiv.19089995
https://doi.org/10.36227/techrxiv.19089995