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» Active learning in very large databases
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FOCS
2008
IEEE
15 years 6 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
CLUSTER
2005
IEEE
15 years 5 months ago
A pipelined data-parallel algorithm for ILP
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly...
Nuno A. Fonseca, Fernando M. A. Silva, Víto...
ICIP
2008
IEEE
15 years 6 months ago
Model-based compression of nonstationary landmark shape sequences
We have proposed a novel model-based compression technique for nonstationary landmark shape data extracted from video sequences. The main goal is to develop a technique for the co...
Samarjit Das, Namrata Vaswani
VLDB
1998
ACM
147views Database» more  VLDB 1998»
15 years 3 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
DAWAK
2004
Springer
15 years 5 months ago
Multidimensional Data Visual Exploration by Interactive Information Segments
Visualization techniques provide an outstanding role in KDD process for data analysis and mining. However, one image does not always convey successfully the inherent information fr...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...