Publications related to Curse of dimensionality

Novel States in Magnetic Materials under Extreme Conditions: A High Pressure Neutron Scattering Study of the Shastry-Sutherland compound SrCu2(BO3)2

This thesis is at the crossing point of dierent elds: Quantum Magnetism which studies the collective properties of low spin systems, Neutron Scattering a powerful technique that enables to probe the microscopic properties of matter, and High Pressure where ...

ETHZ2010

Two-Dimensional Statistical Recoup ling for the Identification of Perturbed Metabolic Networks from NMR Spectroscopy

David Lyndon Emsley

The development of Statistical Total Correlation Spectroscopy (STOCSY), a representation of the autocorrelation matrix of a spectral data set as a 2D pseudospectrum, has allowed more reliable assignment of one- and two-dimensional NMR spectra acquired from ...

AMER CHEMICAL SOC2010

Analysing the temporal dynamics of model performance for hydrological models

Bettina Schaefli

The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can in ...

European Geosciences Union2009

Distributed Similarity Search in High Dimensions Using Locality Sensitive Hashing

Karl Aberer, Sebastian Michel, Parisa Haghani

In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH) which has proven very efficient in answering KNN queries in centralized set ...

2009

SELECTING RELEVANT VISUAL FEATURES FOR SPEECHREADING

Jean-Philippe Thiran, Mihai Gurban, Virginia Estellers Casas

A quantitative measure of relevance is proposed for the task of constructing visual feature sets which are at the same time relevant and compact. A feature's relevance is given by the amount of information that it contains about the problem, while compactn ...

2009

Information theoretic feature extraction for audio-visual speech recognition

Jean-Philippe Thiran, Mihai Gurban

The problem of feature selection has been thoroughly analyzed in the context of pattern classification, with the purpose of avoiding the curse of dimensionality. However, in the context of multimodal signal processing, this problem has been studied less. O ...

2009

Basis Identification from Random Sparse Samples

Rémi Gribonval, Karin Schnass

This article treats the problem of learning a dictionary providing sparse representations for a given signal class, via

\ell_1

minimisation. The problem is to identify a dictionary

\dico

from a set of training samples

\Y

knowing that

\Y = \dico \X

...

2009

Slicing Distributed Systems

Anne-Marie Kermarrec, Vincent Gramoli

Peer-to-peer (P2P) architectures are popular for tasks such as collaborative download, VoIP telephony, and backup. To maximize performance in the face of widely variable storage capacities and bandwidths, such systems typically need to shift work from poor ...

2009

Classification of EEG Signals Using Dempster Shafer Theory and a K-Nearest Neighbor Classiﬁer

Touradj Ebrahimi, Ashkan Yazdani, Ulrich Hoffmann

A brain computer interface (BCI) is a communication system, which translates brain activity into commands for a computer or other devices. Nearly all BCIs contain as a core component a classification algorithm, which is employed to discriminate different b ...

IEEE2009

Observable Subspaces for 3D Human Motion Recovery

Pascal Fua, Mathieu Salzmann, Andrea Fossati

The articulated body models used to represent human motion typically have many degrees of freedom, usually expressed as joint angles that are highly correlated. The true range of motion can therefore be represented by latent variables that span a low-dimen ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Curse of dimensionality

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Novel States in Magnetic Materials under Extreme Conditions: A High Pressure Neutron Scattering Study of the Shastry-Sutherland compound SrCu2(BO3)2

Two-Dimensional Statistical Recoup ling for the Identification of Perturbed Metabolic Networks from NMR Spectroscopy

Analysing the temporal dynamics of model performance for hydrological models

Distributed Similarity Search in High Dimensions Using Locality Sensitive Hashing

SELECTING RELEVANT VISUAL FEATURES FOR SPEECHREADING

Information theoretic feature extraction for audio-visual speech recognition

Basis Identification from Random Sparse Samples

Slicing Distributed Systems

Classification of EEG Signals Using Dempster Shafer Theory and a K-Nearest Neighbor Classiﬁer

Observable Subspaces for 3D Human Motion Recovery

Two-Dimensional Statistical Recoup ling for the Identification of Perturbed Metabolic Networks from NMR Spectroscopy

Analysing the temporal dynamics of model performance for hydrological models

Basis Identification from Random Sparse Samples

SELECTING RELEVANT VISUAL FEATURES FOR SPEECHREADING

Distributed Similarity Search in High Dimensions Using Locality Sensitive Hashing

Classification of EEG Signals Using Dempster Shafer Theory and a K-Nearest Neighbor Classiﬁer

Novel States in Magnetic Materials under Extreme Conditions: A High Pressure Neutron Scattering Study of the Shastry-Sutherland compound SrCu2(BO3)2

Slicing Distributed Systems

Observable Subspaces for 3D Human Motion Recovery

Information theoretic feature extraction for audio-visual speech recognition