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MLDM
2005
Springer
15 years 8 months ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
148
Voted
PKDD
2004
Springer
324views Data Mining» more  PKDD 2004»
15 years 7 months ago
Orange: From Experimental Machine Learning to Interactive Data Mining
Abstract. Orange (www.ailab.si/orange) is a suite for machine learning and data mining. It can be used though scripting in Python or with visual programming in Orange Canvas using ...
Janez Demsar, Blaz Zupan, Gregor Leban, Tomaz Curk
112
Voted
IJCNN
2000
IEEE
15 years 6 months ago
Bias Learning, Knowledge Sharing
—Biasing properly the hypothesis space of a learner has been shown to improve generalization performance. Methods for achieving this goal have been proposed, that range from desi...
Joumana Ghosn, Yoshua Bengio
NIPS
2008
15 years 3 months ago
Hebbian Learning of Bayes Optimal Decisions
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
JMLR
2010
152views more  JMLR 2010»
14 years 9 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...