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POPL
2010
ACM
14 years 2 months ago
Compress-and-conquer for optimal multicore computing
We propose a programming paradigm called compress-and-conquer (CC) that leads to optimal performance on multicore platforms. Given a multicore system of p cores and a problem of s...
Zhijing G. Mou, Hai Liu, Paul Hudak
NN
2000
Springer
128views Neural Networks» more  NN 2000»
13 years 7 months ago
A recurrent neural network for solving linear projection equations
Linear projection equations arise in many optimization problems and have important applications in science and engineering. In this paper, we present a recurrent neural network fo...
Youshen Xia, Jun Wang
CPAIOR
2006
Springer
13 years 11 months ago
The Power of Semidefinite Programming Relaxations for MAX-SAT
Recently, Linear Programming (LP)-based relaxations have been shown promising in boosting the performance of exact MAX-SAT solvers. We compare Semidefinite Programming (SDP) based ...
Carla P. Gomes, Willem Jan van Hoeve, Lucian Leahu
ESOP
2005
Springer
14 years 1 months ago
Interprocedural Herbrand Equalities
We present an aggressive interprocedural analysis for inferring value equalities which are independent of the concrete interpretation of the operator symbols. These equalities, cal...
Markus Müller-Olm, Helmut Seidl, Bernhard Ste...
ICASSP
2010
IEEE
13 years 8 months ago
A robust minimum volume enclosing simplex algorithm for hyperspectral unmixing
Hyperspectral unmixing is a process of extracting hidden spectral signatures (or endmembers) and the corresponding proportions (or abundances) of a scene, from its hyperspectral o...
Arul-Murugan Ambikapathi, Tsung-Han Chan, Wing-Kin...