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» A Paradigm for Parallel Matrix Algorithms:
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ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
14 years 9 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
SOSP
2009
ACM
15 years 7 months ago
Distributed aggregation for data-parallel computing: interfaces and implementations
Data-intensive applications are increasingly designed to execute on large computing clusters. Grouped aggregation is a core primitive of many distributed programming models, and i...
Yuan Yu, Pradeep Kumar Gunda, Michael Isard
SAGT
2009
Springer
131views Game Theory» more  SAGT 2009»
15 years 5 months ago
The Computational Complexity of Weak Saddles
Abstract. We continue the recently initiated study of the computational aspects of weak saddles, an ordinal set-valued solution concept proposed by Shapley. Brandt et al. gave a po...
Felix Brandt, Markus Brill, Felix A. Fischer, Jan ...
PPAM
2007
Springer
15 years 5 months ago
A Supernodal Out-of-Core Sparse Gaussian-Elimination Method
Abstract. We present an out-of-core sparse direct solver for unsymmetric linear systems. The solver factors the coefficient matrix A into A = PLU using Gaussian elimination with pa...
Sivan Toledo, Anatoli Uchitel
PPAM
2005
Springer
15 years 4 months ago
A New Diagonal Blocking Format and Model of Cache Behavior for Sparse Matrices
Algorithms for the sparse matrix-vector multiplication (shortly SpM×V ) are important building blocks in solvers of sparse systems of linear equations. Due to matrix sparsity, the...
Pavel Tvrdík, Ivan Simecek