New research by neuroscientists at the University of Chicago shows that as neurons in this part of the brain process this information, they each respond differently to various features of a surface, creating a
high-dimensional representation of texture in the brain.
The NeuroXM Brain Science Suite lets brain scientists work interactively with
high-dimensional multimodal brain data ranging from neuroimaging to genetics and transcriptomics.
Nonlinear regression with
high-dimensional space mapping for blood component spectral quantitative analysis is discussed in this paper.
They may not effectively excavate the underlying manifold structure which is more beneficial to classification assignment compared with the global structure, if the
high-dimensional samples locate or keep close to a low-dimensional manifold [14,15].
Rovetta, "Clustering
high-dimensional data," in Proceedings of the 1st International Workshop (CHDD'12), pp.
Developing rigorous statistical approaches and implementing innovative computational tools play essential roles in translating the findings based on
high-dimensional -omics data into accurate and informative medical decisions.
In the paper titled "A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for
High-Dimensional Data" A.
For instance, several features obtained from the image datasets are
high-dimensional vectors [1].
This newly developed technology puts to work Fujitsu Laboratories' propriety
high-dimensional statistical analysis technology to estimate the performance of ships actually at sea.
In this paper, we investigate the usability of several dimensionality reduction techniques, such as t-Distributed Stochastic Neighbor Embedding (t-SNE) [2] and Isometric Feature Mapping (Isomap) [3], to create a two- or three-dimensional embedding of the
high-dimensional logged on-board data that are recorded for a HEV fleet, consisting of 6670 passenger cars.
The SPA specifies a method for implementing high-level cognitive systems and behaviors in a
high-dimensional vector space representation, and the NEF specifies methods for implementing vector space representations in spiking neurons.
This article presents a summary of the doctoral dissertation of the author, which addresses the task of machine learning under hubness in intrinsically
high-dimensional data.
