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ICML
2007
IEEE
16 years 3 days ago
Asymptotic Bayesian generalization error when training and test distributions are different
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Keisuke Yamazaki, Klaus-Robert Müller, Masash...
ICML
2002
IEEE
16 years 3 days ago
On generalization bounds, projection profile, and margin distribution
We study generalization properties of linear learning algorithms and develop a data dependent approach that is used to derive generalization bounds that depend on the margin distr...
Ashutosh Garg, Sariel Har-Peled, Dan Roth
CIKM
2004
Springer
15 years 4 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 4 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
MLDM
2007
Springer
15 years 5 months ago
Color Reduction Using the Combination of the Kohonen Self-Organized Feature Map and the Gustafson-Kessel Fuzzy Algorithm
The color reduction in digital images is an active research area in digital image processing. In many applications such as image segmentation, analysis, compression and transmissio...
Konstantinos Zagoris, Nikos Papamarkos, Ioannis Ko...