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KDD
2003
ACM
156views Data Mining» more  KDD 2003»
14 years 4 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
STOC
1998
ACM
190views Algorithms» more  STOC 1998»
13 years 8 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
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 6 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
CSDA
2008
158views more  CSDA 2008»
13 years 4 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner
SIGMOD
2010
ACM
324views Database» more  SIGMOD 2010»
13 years 9 months ago
Similarity search and locality sensitive hashing using ternary content addressable memories
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Rajendra Shinde, Ashish Goel, Pankaj Gupta, Debojy...