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» EM in High Dimensional Spaces
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110
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JMLR
2010
153views more  JMLR 2010»
14 years 5 months ago
Feature Extraction for Outlier Detection in High-Dimensional Spaces
This work addresses the problem of feature extraction for boosting the performance of outlier detectors in high-dimensional spaces. Recent years have observed the prominence of mu...
Nguyen Hoang Vu, Vivekanand Gopalkrishnan
133
Voted
STOC
1998
ACM
190views Algorithms» more  STOC 1998»
15 years 2 months ago
Efficient Search for Approximate Nearest Neighbor in High Dimensional Spaces
We address the problem of designing data structures that allow efficient search for approximate nearest neighbors. More specifically, given a database consisting of a set of vecto...
Eyal Kushilevitz, Rafail Ostrovsky, Yuval Rabani
80
Voted
MASCOTS
2008
14 years 11 months ago
Finding Good Configurations in High-Dimensional Spaces: Doing More with Less
Manually tuning tens to hundreds of configuration parameters in a complex software system like a database or an application server is an arduous task. Recent work has looked into ...
Risi Thonangi, Vamsidhar Thummala, Shivnath Babu
112
Voted
CVPR
1997
IEEE
16 years 8 days ago
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces
Shape indexing is a way of making rapid associations between features detected in an image and object models that could have produced them. When model databases are large, the use...
Jeffrey S. Beis, David G. Lowe
SDM
2009
SIAM
184views Data Mining» more  SDM 2009»
15 years 7 months ago
DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Emmanuel Müller, Ira Assent, Ralph Krieger, S...