The curse of dimensionality refers to various phenomena that arise when analyzing and organizing data in high-dimensional spaces that do not occur in...

Working in high-dimensional spaces can be undesirable for many reasons; raw data are often sparse as a consequence of the curse of dimensionality, and analyzing...

dimensions. The curse of dimensionality is expressed in the order of the integration error that is made by a quadrature of level l {\displaystyle l}...

(mathematical) space. One implication of the curse of dimensionality is that some methods for numerical solution of the Bellman equation require vastly...

of well-known phenomena, which are usually referred to with the umbrella term curse of dimensionality. To assess how severely the dimensionality of a...

problem intractable due to the “curse of dimensionality”. Alternatively, it has been shown that if the cost function of the multi-stage optimization problem...

high-dimensional data, tree-based exact vector search techniques such as the k-d tree and R-tree do not perform well enough because of the curse of dimensionality...

computational cost, the curse of dimensionality, the reliability of random number generators, and the verification and validation of the results. Monte Carlo...

data, it becomes difficult to achieve such high values because of the curse of dimensionality, as the distances become more similar. The silhouette score...

each dimension, complete enumeration of all subspaces becomes intractable with increasing dimensionality. This problem is known as the curse of dimensionality...

k-NN algorithm in order to avoid the effects of the curse of dimensionality. The curse of dimensionality in the k-NN context basically means that Euclidean...

usually referred to as the curse of dimensionality states that there is no general-purpose exact solution for NNS in high-dimensional Euclidean space using...

results in a very sparse vector space of high dimensionality (cf. curse of dimensionality). Reducing the number of dimensions using linear algebraic methods...

Plane of rotation Curse of dimensionality String theory Infinite Hilbert space Function space Dimension (data warehouse) Dimension tables Dimensional analysis...

the curse of dimensionality, but is often embarrassingly parallel because the hyperparameter settings it evaluates are typically independent of each...

models. Because of this, it is less affected by the curse of dimensionality than a p-dimensional smoother. Furthermore, the AM is more flexible than a...

databases. Curse of dimensionality – Difficulties arising when analyzing data with many aspects ("dimensions") Machine learning – Study of algorithms...

clustering, correlation clustering, and the curse of dimensionality. He is one of the founders and core developers of the open-source ELKI data mining framework...

as a way to reduce the dimensionality of high-dimensional data; high-dimensional input items can be reduced to low-dimensional versions while preserving...

number of features that are descriptive of the object. The number of features should not be too large, because of the curse of dimensionality; but should...

\lVert x_{i}-x_{j}\rVert } , it is affected by the curse of dimensionality, and in high dimensional data when distances lose the ability to discriminate...

of the data set. This is often referred to as local intrinsic dimensionality. The intrinsic dimension can be used as a lower bound of what dimension it...

M−1 dimensional space where M is the number of categories. MDA is useful because most classifiers are strongly affected by the curse of dimensionality. In...

Carlo algorithms, when the number of dimensions rises they too tend to suffer the curse of dimensionality: regions of higher probability tend to stretch...

methods and sidestepping the curse of dimensionality during training. Because f j {\displaystyle f_{j}} is taken of a projection of X {\displaystyle X} , the...

typically of order ϵ − d {\displaystyle \epsilon ^{-d}} . That is, the problem suffers the curse of dimensionality. In 1977 P. Boyle, University of Waterloo...

required number of layer and their width can be exponentially smaller. Even if f {\displaystyle f} is not smooth, the curse of dimensionality can be broken...

which struggle with the curse of dimensionality. Deep BSDE methods use neural networks to approximate solutions of high-dimensional partial differential...

Dimension reduction Principal component analysis Multidimensional scaling Cluster-weighted modeling Curse of dimensionality Determining the number of...

Discretization of these values leads to inefficient learning, largely due to the curse of dimensionality. However, there are adaptations of Q-learning that...