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ISPASS
2009
IEEE
16 years 1 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
ICDE
2011
IEEE
258views Database» more  ICDE 2011»
14 years 10 months ago
SystemML: Declarative machine learning on MapReduce
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...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
16 years 12 days ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
JCDL
2006
ACM
161views Education» more  JCDL 2006»
16 years 6 days ago
Learning metadata from the evidence in an on-line citation matching scheme
Citation matching, or the automatic grouping of bibliographic references that refer to the same document, is a data management problem faced by automatic digital libraries for sci...
Isaac G. Councill, Huajing Li, Ziming Zhuang, Sand...
CICLING
2008
Springer
15 years 8 months ago
Unsupervised and Knowledge-Free Learning of Compound Splits and Periphrases
Abstract. We present an approach for knowledge-free and unsupervised recognition of compound nouns for languages that use one-wordcompounds such as Germanic and Scandinavian langua...
Florian Holz, Chris Biemann