NA
2011
12 years 11 months ago
2011
We are interested in computing the Fermi-Dirac matrix function in which the matrix argument is the Hamiltonian matrix arising from Density Function Theory (DFT) applications. More...
MP
2011
12 years 11 months ago
2011
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
MCS
2011
Springer
12 years 11 months ago
2011
Springer
Consider a matrix valued function A(x) ∈ Rm×n , m ≥ n, smoothly depending on parameters x ∈ Ω ⊂ R2 , where Ω is simply connected and bounded. We consider a technique t...
FOCM
2011
12 years 11 months ago
2011
The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding etc. As this problem is NP-hard in ...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Abstract—We consider a certain class of large random matrices, composed of independent column vectors with zero mean and different covariance matrices, and derive asymptotically ...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Wigderson and Xiao presented an efficient derandomization of the matrix Chernoff bound using the method of pessimistic estimators [WX08]. Building on their construction, we prese...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Circulant matrices play a central role in a recently proposed formulation of three-way data computations. In this setting, a three-way table corresponds to a matrix where each “...
CDC
2010
IEEE
12 years 11 months ago
2010
IEEE
Given linear matrix inequalities (LMIs) L1 and L2 in the same number of variables it is natural to ask: (Q1) does one dominate the other, that is, does L1(X) 0 imply L2(X) 0? (Q2) ...
CVPR
2011
IEEE
12 years 12 months ago
2011
IEEE
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
CVPR
2011
IEEE
12 years 12 months ago
2011
IEEE
We consider the problem of fitting one or more subspaces to a collection of data points drawn from the subspaces and corrupted by noise/outliers. We pose this problem as a rank m...