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» Evaluating algorithms that learn from data streams
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SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
15 years 8 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
15 years 5 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
ICCV
2007
IEEE
16 years 1 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
ACL
2012
13 years 9 months ago
Learning Translation Consensus with Structured Label Propagation
In this paper, we address the issue for learning better translation consensus in machine translation (MT) research, and explore the search of translation consensus from similar, r...
Shujie Liu, Chi-Ho Li, Mu Li, Ming Zhou
177
Voted
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Mining social networks for personalized email prioritization
Email is one of the most prevalent communication tools today, and solving the email overload problem is pressingly urgent. A good way to alleviate email overload is to automatical...
Shinjae Yoo, Yiming Yang, Frank Lin, Il-Chul Moon