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» Learning from General Label Constraints
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ICML
2010
IEEE
13 years 6 months ago
Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains
In the realm of multilabel classification (MLC), it has become an opinio communis that optimal predictive performance can only be achieved by learners that explicitly take label d...
Krzysztof Dembczynski, Weiwei Cheng, Eyke Hül...
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 2 months ago
Graph based multi-modality learning
To better understand the content of multimedia, a lot of research efforts have been made on how to learn from multi-modal feature. In this paper, it is studied from a graph point ...
Hanghang Tong, Jingrui He, Mingjing Li, Changshui ...
AROBOTS
2007
159views more  AROBOTS 2007»
13 years 8 months ago
Structure-based color learning on a mobile robot under changing illumination
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
Mohan Sridharan, Peter Stone
VLDB
2003
ACM
165views Database» more  VLDB 2003»
14 years 8 months ago
Learning to match ontologies on the Semantic Web
On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings be...
AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedr...
NIPS
1993
13 years 10 months ago
Surface Learning with Applications to Lipreading
Most connectionist research has focused on learning mappings from one space to another (eg. classification and regression). This paper introduces the more general task of learnin...
Christoph Bregler, Stephen M. Omohundro