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» A general algorithm for data dependence analysis
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PODS
2008
ACM
159views Database» more  PODS 2008»
16 years 11 days ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
CGO
2005
IEEE
15 years 5 months ago
A General Compiler Framework for Speculative Optimizations Using Data Speculative Code Motion
Data speculative optimization refers to code transformations that allow load and store instructions to be moved across potentially dependent memory operations. Existing research w...
Xiaoru Dai, Antonia Zhai, Wei-Chung Hsu, Pen-Chung...
IJFCS
2008
108views more  IJFCS 2008»
15 years 7 days ago
Basic Algorithm for Attribute Implications and Functional Dependencies in Graded Setting
We present GLinClosure, a graded extension of the well-known LinClosure algorithm. GLinClosure can be used to compute degrees of semantic entailment from sets of fuzzy attribute i...
Radim Belohlávek, Vilém Vychodil
83
Voted
ICML
2007
IEEE
16 years 1 months ago
Local dependent components
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Arto Klami, Samuel Kaski
117
Voted
PLDI
2011
ACM
14 years 3 months ago
The tao of parallelism in algorithms
For more than thirty years, the parallel programming community has used the dependence graph as the main abstraction for reasoning about and exploiting parallelism in “regularâ€...
Keshav Pingali, Donald Nguyen, Milind Kulkarni, Ma...