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» Fast matrix rank algorithms and applications
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ICIP
1999
IEEE
15 years 11 months ago
A Fast Algorithm for Rigid Structure from Image Sequences
The factorization method [1] is a feature-based approach to recover 3D rigid structure from motion. In [2], we extended their framework to recover a parametric description of the ...
Pedro M. Q. Aguiar, José M. F. Moura
KDD
2012
ACM
212views Data Mining» more  KDD 2012»
13 years 1 days ago
Fast bregman divergence NMF using taylor expansion and coordinate descent
Non-negative matrix factorization (NMF) provides a lower rank approximation of a matrix. Due to nonnegativity imposed on the factors, it gives a latent structure that is often mor...
Liangda Li, Guy Lebanon, Haesun Park
CORR
2011
Springer
199views Education» more  CORR 2011»
14 years 4 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...
ICCAD
2001
IEEE
124views Hardware» more  ICCAD 2001»
15 years 6 months ago
Highly Accurate Fast Methods for Extraction and Sparsification of Substrate Coupling Based on Low-Rank Approximation
More aggressive design practices have created renewed interest in techniques for analyzing substrate coupling problems. Most previous work has focused primarily on faster techniqu...
Joe Kanapka, Jacob White
MP
2011
14 years 4 months ago
Null space conditions and thresholds for rank minimization
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...
Benjamin Recht, Weiyu Xu, Babak Hassibi