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ML
2006
ACM
163views Machine Learning» more  ML 2006»
13 years 4 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
ICIP
2009
IEEE
13 years 2 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
MICS
2010
134views more  MICS 2010»
13 years 3 months ago
Scale Free Properties of Random k-Trees
Scale free graphs have attracted attention as their non-uniform structure that can be used as a model for many social networks including the WWW and the Internet. In this paper, w...
Colin Cooper, Ryuhei Uehara
CVPR
2007
IEEE
14 years 6 months ago
Learning Visual Similarity Measures for Comparing Never Seen Objects
In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
Eric Nowak, Frédéric Jurie
CORR
2004
Springer
118views Education» more  CORR 2004»
13 years 4 months ago
Understanding Search Trees via Statistical Physics
We study the random m-ary search tree model (where m stands for the number of branches of the search tree), an important problem for data storage in computer science, using a varie...
Satya N. Majumdar, David S. Dean, Paul L. Krapivsk...