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COMPGEOM
2009
ACM
15 years 9 months ago
Approximate center points with proofs
We present the Iterated-Tverberg algorithm, the first deterministic algorithm for computing an approximate centerpoint of a set S ∈ Rd with running time sub-exponential in d. T...
Gary L. Miller, Donald Sheehy
ICDE
2004
IEEE
140views Database» more  ICDE 2004»
16 years 4 months ago
Approximate Aggregation Techniques for Sensor Databases
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collec...
Jeffrey Considine, Feifei Li, George Kollios, John...
STOC
2009
ACM
120views Algorithms» more  STOC 2009»
16 years 3 months ago
A constant-factor approximation for stochastic Steiner forest
We consider the stochastic Steiner forest problem: suppose we were given a collection of Steiner forest instances, and were guaranteed that a random one of these instances would a...
Anupam Gupta, Amit Kumar
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
16 years 3 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
16 years 8 days ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...