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» Active learning in very large databases
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ICDE
2009
IEEE
140views Database» more  ICDE 2009»
16 years 1 months ago
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
One of the most challenging aspects of managing a very large data warehouse is identifying how queries will behave before they start executing. Yet knowing their performance charac...
Archana Ganapathi, Harumi A. Kuno, Umeshwar Dayal,...
DEBU
2000
101views more  DEBU 2000»
14 years 11 months ago
Learning to Understand the Web
In a traditional information retrieval system, it is assumed that queries can be posed about any topic. In reality, a large fraction of web queries are posed about a relatively sm...
William W. Cohen, Andrew McCallum, Dallan Quass
NN
2002
Springer
114views Neural Networks» more  NN 2002»
14 years 11 months ago
Learning the parts of objects by auto-association
Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the parts of o...
Xijin Ge, Shuichi Iwata
DATAMINE
2002
169views more  DATAMINE 2002»
14 years 11 months ago
Advances in Instance Selection for Instance-Based Learning Algorithms
The basic nearest neighbour classifier suffers from the indiscriminate storage of all presented training instances. With a large database of instances classification response time ...
Henry Brighton, Chris Mellish
KDD
2000
ACM
121views Data Mining» more  KDD 2000»
15 years 3 months ago
Mining high-speed data streams
Many organizations today have more than very large databases; they have databases that grow without limit at a rate of several million records per day. Mining these continuous dat...
Pedro Domingos, Geoff Hulten