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» A Framework for Entailed Relation Recognition
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CVPR
2010
IEEE
14 years 9 months ago
Boosting for transfer learning with multiple sources
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
Yi Yao, Gianfranco Doretto
112
Voted
TASLP
2002
156views more  TASLP 2002»
14 years 9 months ago
Musical genre classification of audio signals
Abstract--Musical genres are categorical labels created by humans to characterize pieces of music. A musical genre is characterized by the common characteristics shared by its memb...
George Tzanetakis, Perry R. Cook
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
15 years 3 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
172
Voted
GIS
2008
ACM
15 years 10 months ago
Mining user similarity based on location history
The pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) enable people to conveniently log the location histories they visited with spatio-temporal data. T...
Quannan Li, Yu Zheng, Xing Xie, Yukun Chen, Wenyu ...