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» GraphLab: A New Framework for Parallel Machine Learning
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SIAMIS
2011
13 years 1 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
AAAI
2011
12 years 6 months ago
Logistic Methods for Resource Selection Functions and Presence-Only Species Distribution Models
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they...
Steven Phillips, Jane Elith
CIKM
2011
Springer
12 years 6 months ago
Exploiting longer cycles for link prediction in signed networks
We consider the problem of link prediction in signed networks. Such networks arise on the web in a variety of ways when users can implicitly or explicitly tag their relationship w...
Kai-Yang Chiang, Nagarajan Natarajan, Ambuj Tewari...
BMCBI
2008
118views more  BMCBI 2008»
13 years 6 months ago
Virtual screening of GPCRs: An in silico chemogenomics approach
The G-protein coupled receptor (GPCR) superfamily is currently the largest class of therapeutic targets. In silico prediction of interactions between GPCRs and small molecules is ...
Laurent Jacob, Brice Hoffmann, Véronique St...
SIGIR
2008
ACM
13 years 6 months ago
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization
Multi-document summarization aims to create a compressed summary while retaining the main characteristics of the original set of documents. Many approaches use statistics and mach...
Dingding Wang, Tao Li, Shenghuo Zhu, Chris H. Q. D...