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KDD
2012
ACM
235views Data Mining» more  KDD 2012»
13 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
PADL
2009
Springer
16 years 5 months ago
Using Bloom Filters for Large Scale Gene Sequence Analysis in Haskell
Analysis of biological data often involves large data sets and computationally expensive algorithms. Databases of biological data continue to grow, leading to an increasing demand ...
Ketil Malde, Bryan O'Sullivan
NIPS
2007
15 years 5 months ago
An online Hebbian learning rule that performs Independent Component Analysis
Independent component analysis (ICA) is a powerful method to decouple signals. Most of the algorithms performing ICA do not consider the temporal correlations of the signal, but o...
Claudia Clopath, André Longtin, Wulfram Ger...
AUSAI
2004
Springer
15 years 9 months ago
A Bayesian Metric for Evaluating Machine Learning Algorithms
How to assess the performance of machine learning algorithms is a problem of increasing interest and urgency as the data mining application of myriad algorithms grows. The standard...
Lucas R. Hope, Kevin B. Korb
SAC
2010
ACM
15 years 9 months ago
Of mice and terms: clustering algorithms on ambiguous terms in folksonomies
Developed using the principles of the Model-View-Controller architectural pattern, FolksEngine is a parametric search engine for folksonomies that allows us to test arbitrary sear...
Nicola Raffaele Di Matteo, Silvio Peroni, Fabio Ta...