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CORR
2004
Springer
152views Education» more  CORR 2004»
15 years 12 days ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
ECCC
2006
70views more  ECCC 2006»
15 years 17 days ago
Finding a Heaviest Triangle is not Harder than Matrix Multiplication
We show that for any > 0, a maximum-weight triangle in an undirected graph with n vertices and real weights assigned to vertices can be found in time O(n + n2+), where is the ...
Artur Czumaj, Andrzej Lingas
AAAI
2012
13 years 2 months ago
Sparse Probabilistic Relational Projection
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Wu-Jun Li, Dit-Yan Yeung
PARLE
1994
15 years 4 months ago
Run-Time Optimization of Sparse Matrix-Vector Multiplication on SIMD Machines
Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-v...
Louis H. Ziantz, Can C. Özturan, Boleslaw K. ...
GMP
2006
IEEE
113views Solid Modeling» more  GMP 2006»
15 years 6 months ago
Matrix Based Subdivision Depth Computation for Extra-Ordinary Catmull-Clark Subdivision Surface Patches
Abstract. A new subdivision depth computation technique for extraordinary Catmull-Clark subdivision surface (CCSS) patches is presented. The new technique improves a previous techn...
Gang Chen, Fuhua (Frank) Cheng