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PRL
2008
91views more  PRL 2008»
13 years 7 months ago
Fuzzy relevance vector machine for learning from unbalanced data and noise
Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weightin...
Dingfang Li, Wenchao Hu, Wei Xiong, Jin-Bo Yang
ICPR
2008
IEEE
14 years 2 months ago
Learning combined similarity measures from user data for image retrieval
Image retrieval has become an interesting and active field due to the increasing necessity of searching and browsing very large image repositories. Images are represented using s...
Miguel Arevalillo-Herráez, Francesc J. Ferr...
ACL
2006
13 years 9 months ago
Modeling Commonality among Related Classes in Relation Extraction
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Guodong Zhou, Jian Su, Min Zhang
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
14 years 20 days ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
AAAI
2012
11 years 10 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha