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Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
Submodular meets Spectral Greedy Algorithms for Subset Selection Sparse Approximation Dictionary Selection
2011/3/23
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
Greedy Algorithms Subset Selection Dictionary Selection
2011/3/22
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...
Accounting for Calibration Uncertainties in X-ray Analysis: Effective Areas in Spectral Fitting
Accounting for Calibration Uncertainties Effective Areas in Spectral Fitting X-ray Analysis
2011/3/25
While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a ...
Multiway Spectral Clustering: A Margin-Based Perspective
Spectral clustering spectral relaxation graph partitioning reproducing kernel Hilbert space large-margin classifi ca-tion Gaussian intrinsic autoregression
2011/3/23
Spectral clustering is a broad class of clustering procedures in which an intractable combinatorial optimization formulation of clustering is "relaxed" into a tractable eigenvector problem, and in whi...
Asymptotic distributions and subsampling in spectral analysis for almost periodically correlated time series
α-mixing properties almost periodically correlated time series consistency spectral analysis subsampling
2011/3/21
The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated t...
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Learning (cs.LG) Optimization and Control (math.OC) Machine Learning (stat.ML)
2010/12/17
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...
A Spectral Analysis of Business Cycle Patterns in UK Sectoral Output
business cycle patterns frequency domain
2010/3/9
This paper studies business cycle patterns in UK sectoral output. It analyzes the distinction between white noise processes and their non-white noise counterparts in the frequency domain and further e...
Operator norm convergence of spectral clustering on level sets
Spectral clustering graph unsupervised classification levelsets connected components
2010/3/10
Following Hartigan [1975], a cluster is defined as a connected component of
the t-level set of the underlying density, i.e., the set of points for which the
density is greater than t. A clustering a...
Testing temporal constancy of the spectral structure of a time series
local periodogram non-stationary processes testing time-varying spectral density
2010/3/9
Statistical inference for stochastic processes with time-varying spectral characteristics has received
considerable attention in recent decades.We develop a nonparametric test for stationarity
again...
Spectral estimation of the fractional order of a Lévy process
Regular L´ evy processes Blumenthal–Getoor index semiparametric estimation
2010/3/9
We consider the problem of estimating the fractional order of a
L´evy process from low frequency historical and options data. An estimation
methodology is developed which allows us to treat bo...
Spectral clustering based on local linear approximations
Spectral Clustering Higher-Order Affinities Local Linear Approximation Local PolynomialApproximation
2010/3/9
In the context of clustering, we assume a generative model where each cluster is the result
of sampling points in the neighborhood of an embedded smooth surface, possibly contaminated
with outliers....
Sequential estimation for the spectral density parameter of a stationary Gaussian process
Sequential estimation for the spectral density parameter a stationary Gaussian process
2009/9/24
Sequential estimation for the spectral density parameter of a stationary Gaussian process。
Cumulants for stationary mixing random sequences and applications to empirical spectral density
stationary mixing random sequences applications to empirical spectral density
2009/9/23
Cumulants for stationary mixing random sequences and applications to empirical spectral density。
On Levy (spectral) measures of integral form on Banach spaces
Levy (spectral) measures integral form Banach spaces
2009/9/23
On Levy (spectral) measures of integral form on Banach spaces。
On spectral density estimates for a Gaussian periodically correlated random field
spectral density estimates a Gaussian periodically correlated random field
2009/9/23
On spectral density estimates for a Gaussian periodically correlated random field。