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» A Genetic Algorithm for Clustering on Very Large Data Sets
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ICDE
2011
IEEE
258views Database» more  ICDE 2011»
12 years 11 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
ICML
2009
IEEE
14 years 8 months ago
Online dictionary learning for sparse coding
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
MMDB
2004
ACM
148views Multimedia» more  MMDB 2004»
14 years 1 months ago
A unified framework for image database clustering and content-based retrieval
With the proliferation of image data, the need to search and retrieve images efficiently and accurately from a large image database or a collection of image databases has drastica...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...
GECCO
2003
Springer
148views Optimization» more  GECCO 2003»
14 years 27 days ago
Structural and Functional Sequence Test of Dynamic and State-Based Software with Evolutionary Algorithms
Evolutionary Testing (ET) has been shown to be very successful for testing real world applications [10]. The original ET approach focusesonsearching for a high coverage of the test...
André Baresel, Hartmut Pohlheim, Sadegh Sad...
HAIS
2009
Springer
14 years 9 days ago
Incremental Kernel Machines for Protein Remote Homology Detection
Abstract. Protein membership prediction is a fundamental task to retrieve information for unknown or unidentified sequences. When support vector machines (SVMs) are associated with...
Lionel Morgado, Carlos Pereira