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ICDE
2005
IEEE
107views Database» more  ICDE 2005»
15 years 11 months ago
Venn Sampling: A Novel Prediction Technique for Moving Objects
Given a region qR and a future timestamp qT, a "range aggregate" query estimates the number of objects expected to appear in qR at time qT. Currently the only methods fo...
Yufei Tao, Dimitris Papadias, Jian Zhai, Qing Li
BMVC
2010
14 years 7 months ago
Generalized RBF feature maps for Efficient Detection
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
ESANN
2006
14 years 11 months ago
Using sampling methods to improve binding site predictions
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. In previous work we combine random selection under-sampling with th...
Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhors...
EOR
2007
165views more  EOR 2007»
14 years 9 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
INFOCOM
2006
IEEE
15 years 3 months ago
Sampling Techniques for Large, Dynamic Graphs
— Peer-to-peer systems are becoming increasingly popular, with millions of simultaneous users and a wide range of applications. Understanding existing systems and devising new pe...
Daniel Stutzbach, Reza Rejaie, Nick G. Duffield, S...