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Amaury Lendasse

Researcher at University of Houston

Publications -  315
Citations -  7831

Amaury Lendasse is an academic researcher from University of Houston. The author has contributed to research in topics: Extreme learning machine & Feature selection. The author has an hindex of 39, co-authored 315 publications receiving 7167 citations. Previous affiliations of Amaury Lendasse include Ikerbasque & FedEx Institute of Technology.

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Proceedings ArticleDOI

Towards Developing Visual Statistical Cues for Biodiversity, Abundance, Biomass around Mariana Trench in an Embeddable Smart Module

TL;DR: In this paper, the authors developed ecological indicators in an embeddable smart module, capturing visual statistical cues in biodiversity, abundance, biomass for those primary species observed along deep sea exploration mission, on the basis of RefineDet with our predefined scenic segmentation.
Posted Content

Extreme Learning Tree

TL;DR: A new variant of a decision tree is proposed, called an Extreme Learning Tree, which consists of an extremely random tree with non-linear data transformation, and a linear observer that provides predictions based on the leaf index where the data samples fall.
Book ChapterDOI

ELM Feature Selection and SOM Data Visualization for Nursing Survey Datasets

TL;DR: In this article, the authors presented a novel methodology to analyze nursing surveys based on ELM and SOM to identify which variables lead to the likelihood to report the medication errors, which reduces the curse of dimensionality and improves the interpretability of the visualization.
Proceedings ArticleDOI

Fast variable selection for memetracker phrases time series prediction

TL;DR: This paper proposes a methodology using a fast variable selection as a modified version of the Forward-Backward algorithm adapted to the specificities of the data used: very small number of samples and high number of variables.