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ICCV
2009
IEEE
14 years 9 months ago
Sparse Representation of Cast Shadows via L1-Regularized Least Squares
Scenes with cast shadows can produce complex sets of images. These images cannot be well approximated by lowdimensional linear subspaces. However, in this paper we show that the...
Xue Mei, Haibin Ling, David W. Jacobs
PRL
2011
12 years 11 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
SIAMJO
2010
137views more  SIAMJO 2010»
13 years 3 months ago
Global Convergence of a New Hybrid Gauss--Newton Structured BFGS Method for Nonlinear Least Squares Problems
In this paper, we propose a hybrid Gauss-Newton structured BFGS method with a new update formula and a new switch criterion for the iterative matrix to solve nonlinear least square...
Weijun Zhou, Xiaojun Chen
ISCAS
2008
IEEE
217views Hardware» more  ISCAS 2008»
13 years 11 months ago
Approximate L0 constrained non-negative matrix and tensor factorization
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
Morten Mørup, Kristoffer Hougaard Madsen, L...
SIAMSC
2011
177views more  SIAMSC 2011»
12 years 11 months ago
Computing f(A)b via Least Squares Polynomial Approximations
Given a certain function f, various methods have been proposed in the past for addressing the important problem of computing the matrix-vector product f(A)b without explicitly comp...
Jie Chen, Mihai Anitescu, Yousef Saad