16 search results - page 1 / 4 » Multi-Label Learning by Instance Differentiation |
AAAI
2007
13 years 7 months ago
2007
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
ICTAI
2010
IEEE
13 years 2 months ago
2010
IEEE
Ensemble pruning is concerned with the reduction of the size of an ensemble prior to its combination. Its purpose is to reduce the space and time complexity of the ensemble and/or ...
AAAI
2010
13 years 6 months ago
2010
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
AAAI
2012
11 years 7 months ago
2012
It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the ...
AAAI
2012
11 years 7 months ago
2012
In many real applications, especially those involving data objects with complicated semantics, it is generally desirable to discover the relation between patterns in the input spa...