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» On Feature Extraction via Kernels
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NIPS
2001
13 years 11 months ago
On the Generalization Ability of On-Line Learning Algorithms
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
TKDD
2008
113views more  TKDD 2008»
13 years 10 months ago
Privacy-preserving classification of vertically partitioned data via random kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entiti...
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung
COLING
2008
13 years 11 months ago
Exploiting Constituent Dependencies for Tree Kernel-Based Semantic Relation Extraction
This paper proposes a new approach to dynamically determine the tree span for tree kernel-based semantic relation extraction. It exploits constituent dependencies to keep the node...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
IJON
2007
94views more  IJON 2007»
13 years 9 months ago
A method for speeding up feature extraction based on KPCA
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop...
Yong Xu, David Zhang, Fengxi Song, Jing-Yu Yang, Z...
TRECVID
2007
13 years 11 months ago
MSRA-USTC-SJTU AT TRECVID 2007: HIGH-LEVEL FEATURE EXTRACTION AND SEARCH
This paper describes the MSRA-USTC-SJTU experiments for TRECVID 2007. We performed the experiments in high-level feature extraction and automatic search tasks. For high-level feat...
Tao Mei, Xian-Sheng Hua, Wei Lai, Linjun Yang, Zhe...