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» Using Machine Learning Techniques to Interpret WH-questions
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CIKM
2004
Springer
15 years 6 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 6 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 7 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...
ICPR
2010
IEEE
15 years 7 months ago
A Meta-Learning Approach to Conditional Random Fields Using Error-Correcting Output Codes
—We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a...
Francesco Ciompi, Oriol Pujol, Petia Radeva
ICASSP
2008
IEEE
15 years 7 months ago
Unsupervised learning of auditory filter banks using non-negative matrix factorisation
Non-negative matrix factorisation (NMF) is an unsupervised learning technique that decomposes a non-negative data matrix into a product of two lower rank non-negative matrices. Th...
Alexander Bertrand, Kris Demuynck, Veronique Stout...