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» On Wiedemann's Method of Solving Sparse Linear Systems
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TSP
2010
13 years 3 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
ICCS
2007
Springer
14 years 3 months ago
Hierarchical-Matrix Preconditioners for Parabolic Optimal Control Problems
Abstract. Hierarchical (H)-matrices approximate full or sparse matrices using a hierarchical data sparse format. The corresponding H-matrix arithmetic reduces the time complexity o...
Suely Oliveira, Fang Yang
SIAMJO
2011
13 years 3 months ago
Approximating Semidefinite Packing Programs
In this paper we define semidefinite packing programs and describe an algorithm to approximately solve these problems. Semidefinite packing programs arise in many applications s...
Garud Iyengar, David J. Phillips, Clifford Stein
VALUETOOLS
2006
ACM
176views Hardware» more  VALUETOOLS 2006»
14 years 3 months ago
How to solve large scale deterministic games with mean payoff by policy iteration
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
Vishesh Dhingra, Stephane Gaubert
ICA
2007
Springer
14 years 3 months ago
Sparse Component Analysis in Presence of Noise Using an Iterative EM-MAP Algorithm
Abstract. In this paper, a new algorithm for source recovery in underdetermined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented i...
Hadi Zayyani, Massoud Babaie-Zadeh, G. Hosein Mohi...