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» Approximation Techniques for Spatial Data
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VLDB
2004
ACM
127views Database» more  VLDB 2004»
16 years 4 months ago
Querying high-dimensional data in single-dimensional space
In this paper, we propose a new tunable index scheme, called iMinMax(), that maps points in highdimensional spaces to single-dimensional values determined by their maximum or minim...
Cui Yu, Stéphane Bressan, Beng Chin Ooi, Kian-Lee...
AMC
2008
94views more  AMC 2008»
15 years 4 months ago
Modeling and inversion of net ecological exchange data using an Ito stochastic differential equation approach
A system of stochastic differential equations is studied describing a compartmental carbon transfer model that includes uncertainties arising in the model from environmental and p...
Luther White, Yiqi Luo
IJCNN
2000
IEEE
15 years 9 months ago
Sensor Errors Prediction Using Neural Networks
The features of neural networks using for increasing of an accuracy of physical quantity measurement are considered by prediction of sensor drift. The technique of data volume incr...
Anatoly Sachenko, Volodymyr Kochan, Volodymyr Turc...
AFRIGRAPH
2004
ACM
15 years 10 months ago
Visualizing 3D scenes using non-linear projections and data mining of previous camera movements
We describe techniques for exploring 3D scenes by combining non-linear projections with the interactive data mining of camera navigations from previous explorations. Our approach ...
Karan Singh, Ravin Balakrishnan
ICML
2010
IEEE
15 years 2 months ago
Comparing Clusterings in Space
This paper proposes a new method for comparing clusterings both partitionally and geometrically. Our approach is motivated by the following observation: the vast majority of previ...
Michael H. Coen, M. Hidayath Ansari, Nathanael Fil...