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139
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ICCV
2009
IEEE
16 years 8 months ago
Learning Deformable Action Templates from Crowded Videos
In this paper, we present a Deformable Action Template (DAT) model that is learnable from cluttered real-world videos with weak supervisions. In our generative model, an action ...
Benjamin Yao, Song-Chun Zhu
117
Voted
IRI
2007
IEEE
15 years 9 months ago
BESearch: A Supervised Learning Approach to Search for Molecular Event Participants
Biomedical researchers rely on keyword-based search engines to retrieve superficially relevant documents, from which they must filter out irrelevant information manually. Hence, t...
Richard Tzong-Han Tsai, Hong-Jie Dai, Hsi-Chuan Hu...
135
Voted
CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
15 years 9 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...
113
Voted
CIKM
2008
Springer
15 years 5 months ago
To swing or not to swing: learning when (not) to advertise
Web textual advertising can be interpreted as a search problem over the corpus of ads available for display in a particular context. In contrast to conventional information retrie...
Andrei Z. Broder, Massimiliano Ciaramita, Marcus F...
130
Voted
ICMLA
2008
15 years 4 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...