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COMAD
2008
13 years 8 months ago
Disk-Based Sampling for Outlier Detection in High Dimensional Data
We propose an efficient sampling based outlier detection method for large high-dimensional data. Our method consists of two phases. In the first phase, we combine a "sampling...
Timothy de Vries, Sanjay Chawla, Pei Sun, Gia Vinh...
SIAMCOMP
1998
92views more  SIAMCOMP 1998»
13 years 7 months ago
Surface Approximation and Geometric Partitions
Motivated by applications in computer graphics, visualization, and scienti c computation, we study the computational complexity of the following problem: Given a set S of n points...
Pankaj K. Agarwal, Subhash Suri
AUSDM
2006
Springer
112views Data Mining» more  AUSDM 2006»
13 years 11 months ago
Accuracy Estimation With Clustered Dataset
If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead...
Ricco Rakotomalala, Jean-Hugues Chauchat, Fran&cce...
COMPGEOM
1994
ACM
13 years 11 months ago
Constructing Levels in Arrangements and Higher Order Voronoi Diagrams
We give simple randomized incremental algorithms for computing the k-level in an arrangement of n lines in the plane or in an arrangement of n planes in R3. The expected running ti...
Pankaj K. Agarwal, Mark de Berg, Jirí Matou...
IPSN
2004
Springer
14 years 22 days ago
How to distribute sensors in a random field?
In this paper, we study the optimal way of distributing sensors in a random field to minimize the estimation distortion. We show that this problem is equivalent to certain proble...
Xin Zhang, Stephen B. Wicker