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ICML
2009
IEEE
16 years 20 days ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
15 years 1 months ago
Active Mining of Data Streams
Most previously proposed mining methods on data streams make an unrealistic assumption that "labelled" data stream is readily available and can be mined at anytime. Howe...
Wei Fan, Yi-an Huang, Haixun Wang, Philip S. Yu
KDD
2007
ACM
137views Data Mining» more  KDD 2007»
16 years 8 days ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
KDD
2001
ACM
359views Data Mining» more  KDD 2001»
16 years 7 days ago
Data mining techniques to improve forecast accuracy in airline business
Predictive models developed by applying Data Mining techniques are used to improve forecasting accuracy in the airline business. In order to maximize the revenue on a flight, the ...
Christoph Hueglin, Francesco Vannotti
KDD
2007
ACM
335views Data Mining» more  KDD 2007»
16 years 8 days ago
Detecting changes in large data sets of payment card data: a case study
An important problem in data mining is detecting changes in large data sets. Although there are a variety of change detection algorithms that have been developed, in practice it c...
Chris Curry, Robert L. Grossman, David Locke, Stev...