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AAAI
2010
15 years 10 days ago
Unsupervised Learning of Event Classes from Video
We present a method for unsupervised learning of event classes from videos in which multiple actions might occur simultaneously. It is assumed that all such activities are produce...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
100
Voted
BMCBI
2007
165views more  BMCBI 2007»
14 years 11 months ago
TagSmart: analysis and visualization for yeast mutant fitness data measured by tag microarrays
Background: A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames) of the yeast Saccharomyces cerevisiae has been systematically constructed....
Chulyun Kim, Sangkyum Kim, Russell Dorer, Dan Xie,...
82
Voted
CVPR
2010
IEEE
15 years 3 months ago
On the design of robust classifiers for computer vision
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
Hamed Masnadi-Shirazi, Nuno Vasconcelos, Vijay Mah...
BMCBI
2008
202views more  BMCBI 2008»
14 years 11 months ago
Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data
Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measu...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...
110
Voted
JMLR
2011
192views more  JMLR 2011»
14 years 5 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...