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» Using Anonymized Data for Classification
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132
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CVPR
2008
IEEE
16 years 5 months ago
Semi-supervised boosting using visual similarity learning
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Christian Leistner, Helmut Grabner, Horst Bischof
CHI
2010
ACM
15 years 10 months ago
A case study of micro-blogging in the enterprise: use, value, and related issues
This is a case study about the early adoption and use of micro-blogging in a Fortune 500 company. The study used several independent data sources: five months of empirical micro-b...
Jun Zhang, Yan Qu, Jane Cody, Yulingling Wu
CVPR
2005
IEEE
16 years 5 months ago
Robust Boosting for Learning from Few Examples
We present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of our original data. The motivation is that since the learning algori...
Lior Wolf, Ian Martin
91
Voted
CHI
2006
ACM
16 years 4 months ago
Unified associative information storage and retrieval
We present a novel system for performing information management in a unified manner. Users currently must manage large amounts of data which may be fragmented across file formats ...
Brandon Rothrock, Brad A. Myers, Sophie H. Wang
131
Voted
AUSAI
2007
Springer
15 years 7 months ago
Elements of a Learning Interface for Genre Qualified Search
Even prior to content, the genre of a web document leads to a first coarse binary classification of the recall space in relevant and non-relevant documents. Thinking of a genre se...
Andrea Stubbe, Christoph Ringlstetter, Randy Goebe...