In this paper, we propose a tree-structured multiclass classifier to identify annotations and overlapping text from machine printed documents. Each node of the tree-structured cla...
—We introduce quantization feature functions to represent continuous or large range discrete data into the symbolic CRF data representation. We show that doing this convertion in...
Transfer learning aims to solve new learning problems by extracting and making use of the common knowledge found in related domains. A key element of transfer learning is to ident...
Qiang Yang, Vincent Wenchen Zheng, Bin Li, Hankz H...
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
We identify privacy risks associated with releasing network data sets and provide an algorithm that mitigates those risks. A network consists of entities connected by links repres...
Michael Hay, Gerome Miklau, David Jensen, Donald F...