搜索结果: 1-15 共查到“数学 Clustering”相关记录16条 . 查询时间(0.147 秒)
Reconstruction and Clustering in Random Constraint Satisfaction Problems
Random quantity structure solution space threshold
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2015/8/20
Random instances of Constraint Satisfaction Problems (CSP’s) appear to be hard for all known algorithms, when the number of constraints per variable lies in a certain interval. Contributing to the gen...
Clustering with mixtures of log-concave distributions
EM algorithm Log-concave distribution Clustering Normal copula
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2015/8/20
The EM algorithm is a popular tool for clustering observations via a parametric mixture model. Two disadvantages of this
approach are that its success depends on the appropriateness of the assumed pa...
A Geometric Analysis of Subspace Clustering with Outliers
Subspace clustering spectral clustering outlier detection `1 minimization duality in linear programming geometric functional analysis properties of convex bodies concentration of measure
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2015/6/17
This paper considers the problem of clustering a collection of unlabeled data points assumed to lie near a union of lower dimensional planes. As is common in computer vision or unsupervised learning a...
Robust Subspace Clustering
Subspace clustering spectral clustering LASSO Dantzig selector `1 minimization multiple hypothesis testing true and false discoveries geometric functional analysis nonasymptotic random matrix theory
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2015/6/17
Subspace clustering refers to the task of finding a multi-subspace representation that best fits a collection of points taken from a high-dimensional space. This paper introduces an algorithm inspired...
Assortativity and clustering of sparse random intersection graphs
assortativity clustering power law random graph random intersection graph 2010 Mathematics Subject Classifications 05C80 05C82 91D30
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2012/11/23
We consider sparse random intersection graphs with the property that the clustering coefficient does not vanish as the number of nodes tends to infinity. We find explicit asymptotic expressions for th...
Topological graph clustering with thin position
Thin position data mining graph partitioning
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2012/6/21
A clustering algorithm partitions a set of data points into smaller sets (clusters) such that each subset is more tightly packed than the whole. Many approaches to clustering translate the vector data...
An invariant in shock clustering and Burgers turbulence
Shock clustering stochastic coalescence kinetic theory Burgers turbulence integrable systems Loitsiansky invariant
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2011/7/6
1-D scalar conservation laws with convex flux and Markov initial data
are now known to yield a completely integrable Hamiltonian system. In
this article, we rederive the analogue of Loitsiansky’s in...
Non-Gaussian gravitational clustering field statistics
large-scale structure of Universe – galaxies clusters
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2011/3/2
In this work we investigate the multivariate statistical description of the matter distribution
in the nonlinear regime.
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Inverse Power Method for Nonlinear Eigenproblems Applications 1-Spectral Clustering Sparse PCA
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2011/3/2
Many problems in machine learning and statistics can be formulated as (generalized)eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding crit...
Non-Gaussian gravitational clustering field statistics
Non-Gaussian gravitational clustering field statistics
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2011/1/4
In this work we investigate the multivariate statistical description of the matter distribution in the nonlinear regime. We introduce the multivariate Edgeworth expansion of the lognormal distribution...
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Inverse Power Method Nonlinear Eigenproblems
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2011/1/4
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding cri...
Clustering with or without the Approximation
Clustering Approximation
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2012/12/3
We study algorithms for clustering data that were recently proposed by Balcan, Blum and Gupta in SODA’09 [4] and that have already given rise to two follow-up papers. The input for the clustering prob...
A new space-time model for volatility clustering in the financial market
space-time model volatility clustering financial market
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2010/4/27
A new space-time model for interacting agents on the financial market is presented. It is a combination of the Curie-Weiss model and a space-time model introduced by J\"arpe 2005. Properties of the mo...
Asset returns and volatility clustering in financial time series
volatility clustering financial time series
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2010/4/27
An analysis of the stylized facts in financial time series is carried out. We find that, instead of the heavy tails in asset return distributions, the slow decay behaviour in autocorrelation functions...
Clustering of exponentially separating trajectories
exponentially separating trajectories deterministic maps
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2010/4/1
It might be expected that trajectories for a dynamical system which has no negative Lyapunov exponent (implying exponential growth of small separations will not cluster together. However, clustering c...