5115 search results - page 237 / 1023 » On Randomized Lanczos Algorithms |
202
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ECCV
2010
Springer
15 years 7 months ago
2010
Springer
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
291
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ICIP
2010
IEEE
15 years 5 months ago
2010
IEEE
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
184
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ASPDAC
2009
ACM
16 years 1 months ago
2009
ACM
— Power distribution networks (PDNs) are designed and analyzed iteratively. Random walk is among the most efficient methods for PDN analysis. We develop in this paper an increme...
217
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MIR
2005
ACM
16 years 18 days ago
2005
ACM
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
268
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BMCBI
2007
15 years 7 months ago
2007
Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and relate...