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ICASSP
2009
IEEE
14 years 7 months ago
Weighted nonnegative matrix factorization
Nonnegative matrix factorization (NMF) is a widely-used method for low-rank approximation (LRA) of a nonnegative matrix (matrix with only nonnegative entries), where nonnegativity...
Yong-Deok Kim, Seungjin Choi
ICASSP
2011
IEEE
14 years 1 months ago
An efficient rank-deficient computation of the Principle of Relevant Information
One of the main difficulties in computing information theoretic learning (ITL) estimators is the computational complexity that grows quadratically with data. Considerable amount ...
Luis Gonzalo Sánchez Giraldo, José C...
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 3 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
83
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ECCV
2002
Springer
15 years 11 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto
CEC
2009
IEEE
15 years 4 months ago
Enhancing MOEA/D with guided mutation and priority update for multi-objective optimization
—Multi-objective optimization is an essential and challenging topic in the domains of engineering and computation because real-world problems usually include several conflicting...
Chih-Ming Chen, Ying-Ping Chen, Qingfu Zhang