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AIM
2011
10 years 8 months ago
Transfer Learning by Reusing Structured Knowledge
Transfer learning aims to solve new learning problems by extracting and making use of the common knowledge found in related domains. A key element of transfer learning is to ident...
Qiang Yang, Vincent Wenchen Zheng, Bin Li, Hankz H...
WSDM
2012
ACM
325views Data Mining» more  WSDM 2012»
10 years 22 days ago
Coupled temporal scoping of relational facts
Recent research has made signi´Čücant advances in automatically constructing knowledge bases by extracting relational facts (e.g., Bill Clinton-presidentOf-US) from large text cor...
Partha Pratim Talukdar, Derry Tanti Wijaya, Tom Mi...
AAAI
2010
11 years 6 months ago
Adaptive Transfer Learning
Transfer learning aims at reusing the knowledge in some source tasks to improve the learning of a target task. Many transfer learning methods assume that the source tasks and the ...
Bin Cao, Sinno Jialin Pan, Yu Zhang, Dit-Yan Yeung...
ECCV
2008
Springer
12 years 7 months ago
Scale Invariant Action Recognition Using Compound Features Mined from Dense Spatio-temporal Corners
Abstract. The use of sparse invariant features to recognise classes of actions or objects has become common in the literature. However, features are often "engineered" to...
Andrew Gilbert, John Illingworth, Richard Bowden
ICMLA
2009
11 years 2 months ago
Knowledge Transfer for Feature Generation in Document Classification
One important problem in machine learning is how to extract knowledge from prior experience, then transfer and apply this knowledge in new learning tasks. To address this problem, ...
Jian Zhang, Shobhit S. Shakya
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