[图书][B] Introduction to high-dimensional statistics
C Giraud - 2021 - taylorfrancis.com
… The statistical reality unfortunately clashes with this optimistic statement: Separating the
signal from the noise is in general almost impossible in high-dimensional data. This …
signal from the noise is in general almost impossible in high-dimensional data. This …
[PDF][PDF] Learning high-dimensional data
M Verleysen - Nato Science Series Sub Series III Computer …, 2003 - perso.uclouvain.be
… high-dimensional spaces can behave in a drastically different way from our intuition (mostly
gained from … not to remove the difficulties related to high-dimensional data, but to circumvent …
gained from … not to remove the difficulties related to high-dimensional data, but to circumvent …
On almost linearity of low dimensional projections from high dimensional data
P Hall, KC Li - The annals of Statistics, 1993 - JSTOR
… our ability to extract useful information from high dimensional data. There are several … ,
statisticians can now easily interact with the high dimensional data by 3-D rotation plots, …
statisticians can now easily interact with the high dimensional data by 3-D rotation plots, …
Visualizing large-scale and high-dimensional data
… from considerable computational costs, preventing the state-ofthe-art methods such as the
t-SNE from scaling to largescale and high-dimensional … -nearest neighbor graph from the data …
t-SNE from scaling to largescale and high-dimensional … -nearest neighbor graph from the data …
Statistical challenges of high-dimensional data
IM Johnstone, DM Titterington - … Transactions of the …, 2009 - royalsocietypublishing.org
… that arise with high-dimensional data in the … , from within a very large set, the variables
that help to classify observations. Brief mention is made of the visualization of high-dimensional …
that help to classify observations. Brief mention is made of the visualization of high-dimensional …
The properties of high-dimensional data spaces: implications for exploring gene and protein expression data
… statistical and biological information from high-dimensional data spaces, … From the
perspective of translational science, this Review discusses the properties of high-dimensional …
perspective of translational science, this Review discusses the properties of high-dimensional …
Bioinspired materials: from low to high dimensional structure
N Zhao, Z Wang, C Cai, H Shen, F Liang… - Advanced …, 2014 - Wiley Online Library
… and their amazing properties largely result from the sophisticated hierarchical structures.
Following … with the emphasis on mimicking the structure from one to three dimensions. Selected …
Following … with the emphasis on mimicking the structure from one to three dimensions. Selected …
Learning to classify from impure samples with high-dimensional data
… Here, we demonstrate that complex, high-dimensional classifiers can also be trained on …
avoid relying exclusively on simulations for high-dimensional classification. This work opens the …
avoid relying exclusively on simulations for high-dimensional classification. This work opens the …
Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
… to each other than cells from other clusters. Because these … correlations in high-dimensional
data (m ≥ 3) from a series … to extract a hierarchy from high-dimensional cytometry data in …
data (m ≥ 3) from a series … to extract a hierarchy from high-dimensional cytometry data in …
Extracting sparse high-dimensional dynamics from limited data
… of physical models and mathematical equations directly from data is becoming increasingly
possible… high-dimensional differential equations (which we will refer to as the ``model"") from …
possible… high-dimensional differential equations (which we will refer to as the ``model"") from …