2019•Information SciencesOpen access

A manifold learning approach to dimensionality reduction for modeling data

Claudio Turchetti, Laura Falaschetti

Open full text 35 citations

Abstract

This record does not include an abstract. Use the full-text link above if available.

About this research paper

What this paper is about

An abstract is not available in the OpenAlex record for this paper.

Why it matters

OpenAlex reports 35 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Key concepts: Dimensionality reduction, Nonlinear dimensionality reduction, Intrinsic dimension, Curse of dimensionality, Manifold (fluid mechanics), Context (archaeology), Embedding, Dimension (graph theory)