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Tensor Decompositions: A New Concept in Brain Data Analysis?
Multilinear BSS linked multiway BSS/ICA tensor factorizations and de-compositions constrained Tucker and CP models PenalizedTensor Decompositions (PTD) feature extraction classification multiway PLS and CCA
2013/6/14
Matrix factorizations and their extensions to tensor factorizations and decompositions have become prominent techniques for linear and multilinear blind source separation (BSS), especially multiway In...
Complexity penalized hydraulic fracture localization and moment tensor estimation under limited model information
Complexity penalized hydraulic fracture localization moment tensor estimation limited model information
2013/6/14
In this paper we present a novel technique for micro-seismic localization using a group sparse penalization that is robust to the focal mechanism of the source and requires only a velocity model of th...
Convex Tensor Decomposition via Structured Schatten Norm Regularization
Convex Tensor Decomposition Structured Schatten Norm Regularization
2013/4/28
We discuss structured Schatten norms for tensor decomposition that includes two recently proposed norms ("overlapped" and "latent") for convex-optimization-based tensor decomposition, and connect tens...
Partially monotone tensor spline estimation of the joint distribution function with bivariate current status data
Bivariate current status data constrained maximum likelihood estimation empirical process sieve maximum likelihood estimation tensor spline basis functions
2012/11/23
The analysis of the joint cumulative distribution function (CDF) with bivariate event time data is a challenging problem both theoretically and numerically. This paper develops a tensor spline-based s...
Cramer-Rao-Induced Bounds for CANDECOMP/PARAFAC tensor decomposition
CANDECOMP/PARAFAC Cramer-Rao-Induced tensor decomposition Bounds
2012/11/22
This paper presents a Cramer-Rao lower bound (CRLB) on the variance of unbiased estimates of factor matrices in Canonical Polyadic (CP) or CANDECOMP/PARAFAC (CP) decompositions of a tensor from noisy ...
All-at-once Optimization for Coupled Matrix and Tensor Factorizations
data fusion matrix factorizations tensor factorizations CANDECOMP PARAFAC missing data
2011/6/21
Joint analysis of data from multiple sources has the potential
to improve our understanding of the underlying structures
in complex data sets. For instance, in restaurant recommendation
systems, re...
Making Tensor Factorizations Robust to Non-Gaussian Noise
Making Tensor Factorizations Robust Non-Gaussian Noise
2010/10/19
Tensors are multi-way arrays, and the Candecomp/Parafac (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective functio...
The existence of the effective diffusivity tensor for diffusions with incompressible mixing drifts
Random field diffusions in random media mixing
2009/9/21
In the present article we consider a model of motion of
a passive tracer particle under a random, non-steady (time dependent),
incompressible velocity flow in a medium with positive molecular diffus...
Asymptotic study of canonical correlation analysis：from matrix and analytic approach to operator and tensor approach
multivariate analysis canonical correlation analysis asymptotic study operator coordinatefree distribution-free
2009/2/23
Asymptotic study of canonical correlation analysis gives the opportunity to present the different steps of an asymptotic study and to show the interest of an operator and tensor approach of multidimen...