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» On k-Anonymity and the Curse of Dimensionality
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KDD
2008
ACM
234views Data Mining» more  KDD 2008»
15 years 9 months ago
Angle-based outlier detection in high-dimensional data
Detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. All...
Hans-Peter Kriegel, Matthias Schubert, Arthur Zime...
DAGSTUHL
2009
14 years 10 months ago
Advances in Feature Selection with Mutual Information
The selection of features that are relevant for a prediction or classification problem is an important problem in many domains involving high-dimensional data. Selecting features h...
Michel Verleysen, Fabrice Rossi, Damien Fran&ccedi...
CDC
2008
IEEE
137views Control Systems» more  CDC 2008»
15 years 3 months ago
An approximate dynamic programming approach to probabilistic reachability for stochastic hybrid systems
— This paper addresses the computational overhead involved in probabilistic reachability computations for a general class of controlled stochastic hybrid systems. An approximate ...
Alessandro Abate, Maria Prandini, John Lygeros, Sh...
ACIVS
2009
Springer
15 years 2 months ago
A New Feasible Approach to Multi-dimensional Scale Saliency
In this paper, we present a multi-dimensional extension of an image feature extractor, the scale saliency algorithm by Kadir and Brady. In order to avoid the curse of dimensionalit...
Pablo Suau, Francisco Escolano
BSN
2006
IEEE
150views Sensor Networks» more  BSN 2006»
15 years 1 months ago
Multi-sensor Data Fusion Using the Influence Model
System robustness against individual sensor failures is an important concern in multi-sensor networks. Unfortunately, the complexity of using the remaining sensors to interpolate ...
Wen Dong, Alex Pentland