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EWCBR
2006
Springer
15 years 10 months ago
Unsupervised Feature Selection for Text Data
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
DAS
2006
Springer
15 years 8 months ago
Extraction and Analysis of Document Examiner Features from Vector Skeletons of Grapheme 'th'
Abstract. This paper presents a study of 25 structural features extracted from samples of grapheme `th' that correspond to features commonly used by forensic document examiner...
Vladimir Pervouchine, Graham Leedham
AAAI
2010
15 years 8 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu
ICML
2010
IEEE
15 years 8 months ago
Online Streaming Feature Selection
We study an interesting and challenging problem, online streaming feature selection, in which the size of the feature set is unknown, and not all features are available for learni...
Xindong Wu, Kui Yu, Hao Wang, Wei Ding
CVPR
2009
IEEE
17 years 2 months ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...