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DIS
2006
Springer
15 years 1 months ago
Incremental Algorithm Driven by Error Margins
Incremental learning is an approach to deal with the classification task when datasets are too large or when new examples can arrive at any time. One possible approach uses concent...
Gonzalo Ramos-Jiménez, José del Camp...
ECCB
2008
IEEE
15 years 4 months ago
Functional coherence in domain interaction networks
Motivation: Extracting functional information from protein–protein interactions (PPI) poses significant challenges arising from the noisy, incomplete, generic and static nature...
Jayesh Pandey, Mehmet Koyutürk, Shankar Subra...
ICPR
2010
IEEE
15 years 3 months ago
On-Line Random Naive Bayes for Tracking
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...
CIKM
2005
Springer
15 years 3 months ago
Rotation invariant indexing of shapes and line drawings
We present data representations, distance measures and organizational structures for fast and efficient retrieval of similar shapes in image databases. Using the Hough Transform w...
Michail Vlachos, Zografoula Vagena, Philip S. Yu, ...
GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
15 years 3 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu