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» Learning to rank from Bayesian decision inference
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JAIR
2010
145views more  JAIR 2010»
13 years 6 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint
ACL
2009
13 years 5 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay
TCSV
2011
13 years 2 months ago
Integrating Spatio-Temporal Context With Multiview Representation for Object Recognition in Visual Surveillance
—We present in this paper an integrated solution to rapidly recognizing dynamic objects in surveillance videos by exploring various contextual information. This solution consists...
Xiaobai Liu, Liang Lin, Shuicheng Yan, Hai Jin, We...
TRECVID
2008
13 years 9 months ago
LIG and LIRIS at TRECVID 2008: High Level Feature Extraction and Collaborative Annotation
This paper describes our participations of LIG and LIRIS to the TRECVID 2008 High Level Features detection task. We evaluated several fusion strategies and especially rank fusion....
UM
2010
Springer
13 years 11 months ago
Interaction and Personalization of Criteria in Recommender Systems
A user’s informational need and preferences can be modeled by criteria, which in turn can be used to prioritize candidate results and produce a ranked list. We examine the use of...
Shawn R. Wolfe, Yi Zhang