30 search results - page 3 / 6 » Parallel Learning of Large Fuzzy Cognitive Maps |
SIGMOD
2007
ACM
14 years 5 months ago
2007
ACM
Map-Reduce is a programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. Through ...
SC
2009
ACM
14 years 17 days ago
2009
ACM
In this paper, we discuss some of the lessons that we have learned working with the Hadoop and Sector/Sphere systems. Both of these systems are cloud-based systems designed to sup...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuf...
ICDE
2011
IEEE
12 years 9 months ago
2011
IEEE
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
APPT
2009
Springer
14 years 10 days ago
2009
Springer
MapReduce has been prevalent for running data-parallel applications. By hiding other non-functionality parts such as parallelism, fault tolerance and load balance from programmers,...