Concept

Curse of dimensionality

Related publications (331)

Learning Low-Dimensional Signal Models

Sampling, coding, and streaming even the most essential data, e.g., in medical imaging and weather-monitoring applications, produce a data deluge that severely stresses the avail able analog-to-digital converter, communication bandwidth, and digital-storag ...

Institute of Electrical and Electronics Engineers2011

Nonlocal Means With Dimensionality Reduction and SURE-Based Parameter Selection

Dimitri Nestor Alice Van De Ville, Michel Kocher

Nonlocal means (NLM) is an effective denoising method that applies adaptive averaging based on similarity between neighborhoods in the image. An attractive way to both improve and speed-up NLM is by first performing a linear projection of the neighborhood. ...

IEEE2011

Grassmann Hashing For Approximate Nearest Neighbor Search In High Dimensional Space

Lei Zhang, Xinchao Wang

Locality-Sensitive Hashing (LSH) approximates nearest neighbors in high dimensions by projecting original data into low-dimensional subspaces. The basic idea is to hash data samples to ensure that the probability of collision is much higher for samples tha ...

Ieee2011

SpaCEM(3): a software for biological module detection when data is incomplete, high dimensional and dependent

Juliette Ferial Blanchet

Summary: Among classical methods for module detection, SpaCEM3 provides ad hoc algorithms that were shown to be particularly well adapted to specific features of biological data: high-dimensionality, interactions between components (genes) and integrated t ...

2011

Linear Manifold Approximation based on Differences of Tangents

Pascal Frossard, Sofia Karygianni

In this paper, we consider the problem of manifold approximation with affine subspaces. Our objective is to discover a set of low dimensional affine subspaces that represents manifold data accurately while preserving the manifold’s structure. For this purp ...

2011

Certified Reduced Basis Approximation for Parametrized Partial Differential Equations and Applications

Alfio Quarteroni, Gianluigi Rozza, Andrea Manzoni

Reduction strategies, such as model order reduction (MOR) or reduced basis (RB) methods, in scientic computing may become crucial in applications of increasing complexity. In this paper we review the reduced basis method (built upon a high-delity "truth" f ...

2011

Pair correlations, short-range order, and dispersive excitations in the quasi-kagome quantum magnet volborthite

Henrik Moodysson Rønnow, Goran Nilsen

We present spatial and dynamic information on the s = 1/2 distorted kagome antiferromagnet volborthite, Cu3V2O7(OD)(2) center dot 2D(2)O, obtained by polarized and inelastic neutron scattering. The instantaneous structure factor, S(Q), is dominated by near ...

2011

Distributed processing of continuous sliding-window k-NN queries for data stream filtering

Karl Aberer, Ivana Podnar, Kresimir Pripuzic

A sliding-window k-NN query (k-NN/w query) continuously monitors incoming data stream objects within a sliding window to identify k closest objects to a query. It enables effective filtering of data objects streaming in at high rates from potentially distr ...

Springer Verlag2011

Online performance guarantees for sparse recovery

Volkan Cevher

A K*-sparse vector x* ∈ RN produces measurements via linear dimensionality reduction as u = Φx* +n, where Φ ∈ RM×N (M

2011

Biologically inspired kinematic synergies enable linear balance control of a humanoid robot

Auke Ijspeert

Despite many efforts, balance control of humanoid robots in the presence of unforeseen external or internal forces has remained an unsolved problem. The difficulty of this problem is a consequence of the high dimensionality of the action space of a humanoi ...

2011

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