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The nas parallel benchmarks
 The International Journal of Supercomputer Applications
, 1991
"... A new set of benchmarks has been developed for the performance evaluation of highly parallel supercomputers. These benchmarks consist of ve \parallel kernel " benchmarks and three \simulated application" benchmarks. Together they mimic the computation and data movement characterist ..."
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Cited by 686 (10 self)
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A new set of benchmarks has been developed for the performance evaluation of highly parallel supercomputers. These benchmarks consist of ve \parallel kernel " benchmarks and three \simulated application" benchmarks. Together they mimic the computation and data movement
UNet: A UserLevel Network Interface for Parallel and Distributed Computing
 In Fifteenth ACM Symposium on Operating System Principles
, 1995
"... The UNet communication architecture provides processes with a virtual view of a network interface to enable userlevel access to highspeed communication devices. The architecture, implemented on standard workstations using offtheshelf ATM communication hardware, removes the kernel from the communi ..."
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Cited by 596 (17 self)
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performance equivalent to Meiko CS2 and TMC CM5 supercomputers on a set of SplitC benchmarks. 1
DominanceBased Rough Sets Using Indexed Blocks as
"... Abstract. Dominancebased rough set introduced by Greco et al. is an extension of Pawlak’s classical rough set theory by using dominance relations in place of equivalence relations for approximating sets of preference ordered decision classes satisfying upward and downward union properties. This pa ..."
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Abstract. Dominancebased rough set introduced by Greco et al. is an extension of Pawlak’s classical rough set theory by using dominance relations in place of equivalence relations for approximating sets of preference ordered decision classes satisfying upward and downward union properties
LogP: Towards a Realistic Model of Parallel Computation
, 1993
"... A vast body of theoretical research has focused either on overly simplistic models of parallel computation, notably the PRAM, or overly specific models that have few representatives in the real world. Both kinds of models encourage exploitation of formal loopholes, rather than rewarding developme ..."
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Cited by 562 (15 self)
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parallel algorithms and to offer guidelines to machine designers. Such a model must strike a balance between detail and simplicity in order to reveal important bottlenecks without making analysis of interesting problems intractable. The model is based on four parameters that specify abstractly
A Threshold of ln n for Approximating Set Cover
 JOURNAL OF THE ACM
, 1998
"... Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NPhar ..."
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Cited by 778 (5 self)
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Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NP
Machine Learning in Automated Text Categorization
 ACM COMPUTING SURVEYS
, 2002
"... The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this p ..."
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Cited by 1658 (22 self)
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to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual
Image denoising using a scale mixture of Gaussians in the wavelet domain
 IEEE TRANS IMAGE PROCESSING
, 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
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Cited by 514 (17 self)
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We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian
A Fast and Elitist MultiObjective Genetic Algorithm: NSGAII
, 2000
"... Multiobjective evolutionary algorithms which use nondominated sorting and sharing have been mainly criticized for their (i) O(MN computational complexity (where M is the number of objectives and N is the population size), (ii) nonelitism approach, and (iii) the need for specifying a sharing param ..."
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Cited by 1707 (58 self)
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parameter. In this paper, we suggest a nondominated sorting based multiobjective evolutionary algorithm (we called it the Nondominated Sorting GAII or NSGAII) which alleviates all the above three difficulties. Specifically, a fast nondominated sorting approach with O(MN ) computational complexity
Functional discovery via a compendium of expression profiles. Cell 102:109
, 2000
"... have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of ..."
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Cited by 537 (8 self)
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have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of
A Fast Elitist NonDominated Sorting Genetic Algorithm for MultiObjective Optimization: NSGAII
, 2000
"... Multiobjective evolutionary algorithms which use nondominated sorting and sharing have been mainly criticized for their (i) 4 computational complexity (where is the number of objectives and is the population size), (ii) nonelitism approach, and (iii) the need for specifying a sharing ..."
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Cited by 634 (15 self)
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sharing parameter. In this paper, we suggest a nondominated sorting based multiobjective evolutionary algorithm (we called it the Nondominated Sorting GAII or NSGAII) which alleviates all the above three difficulties. Specifically, a fast nondominated sorting approach with computational
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