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EUROPAR
1998
Springer
13 years 10 months ago
Parallel Sparse Matrix Computations Using the PINEAPL Library: A Performance Study
Abstract. The Numerical Algorithms Group Ltd is currently participating in the European HPCN Fourth Framework project on Parallel Industrial NumErical Applications and Portable Lib...
Arnold R. Krommer
IMC
2004
ACM
13 years 11 months ago
Modeling distances in large-scale networks by matrix factorization
In this paper, we propose a model for representing and predicting distances in large-scale networks by matrix factorization. The model is useful for network distance sensitive app...
Yun Mao, Lawrence K. Saul
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 2 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre
JMLR
2010
147views more  JMLR 2010»
13 years 23 days ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
SC
2005
ACM
13 years 11 months ago
Tera-Scalable Algorithms for Variable-Density Elliptic Hydrodynamics with Spectral Accuracy
We describe Miranda, a massively parallel spectral/compact solver for variabledensity incompressible flow, including viscosity and species diffusivity effects. Miranda utilizes...
Andrew W. Cook, William H. Cabot, Peter L. William...