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» Computing LTS Regression for Large Data Sets
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ISVC
2007
Springer
15 years 10 months ago
Learning to Recognize Complex Actions Using Conditional Random Fields
Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple...
Christopher I. Connolly
PKDD
2007
Springer
147views Data Mining» more  PKDD 2007»
15 years 10 months ago
MINI: Mining Informative Non-redundant Itemsets
Frequent itemset mining assists the data mining practitioner in searching for strongly associated items (and transactions) in large transaction databases. Since the number of frequ...
Arianna Gallo, Tijl De Bie, Nello Cristianini
NIPS
2001
15 years 5 months ago
Grammatical Bigrams
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Mark A. Paskin
COMCOM
2010
179views more  COMCOM 2010»
15 years 4 months ago
On the statistical characterization of flows in Internet traffic with application to sampling
A new method of estimating some statistical characteristics of TCP flows in the Internet is developed in this paper. For this purpose, a new set of random variables (referred to as...
Yousra Chabchoub, Christine Fricker, Fabrice Guill...
ARTMED
2002
92views more  ARTMED 2002»
15 years 3 months ago
Predicting glaucomatous visual field deterioration through short multivariate time series modelling
In bio-medical domains there are many applications involving the modelling of multivariate time series (MTS) data. One area that has been largely overlooked so far is the particul...
Stephen Swift, Xiaohui Liu