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ICCV
2009
IEEE
16 years 11 months ago
Domain Adaptive Semantic Diffusion for Large Scale Context-Based Video Annotation
Learning to cope with domain change has been known as a challenging problem in many real-world applications. This paper proposes a novel and efficient approach, named domain ada...
Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah ...
CVPR
2009
IEEE
17 years 1 months ago
Learning from Ambiguously Labeled Images
In many image and video collections, we have access only to partially labeled data. For example, personal photo collections often contain several faces per image and a caption t...
Benjamin Sapp, Benjamin Taskar, Chris Jordan, Timo...
ICML
2006
IEEE
16 years 7 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
CIKM
2007
Springer
16 years 25 days ago
Developing learning strategies for topic-based summarization
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
Ouyang You, Sujian Li, Wenjie Li
ECSQARU
2005
Springer
16 years 6 days ago
On the Use of Restrictions for Learning Bayesian Networks
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
Luis M. de Campos, Javier Gomez Castellano