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JMLR
2006
131views more  JMLR 2006»
13 years 7 months ago
Incremental Support Vector Learning: Analysis, Implementation and Applications
Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM ...
Pavel Laskov, Christian Gehl, Stefan Krüger, ...
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
11 years 10 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
DAGM
2006
Springer
13 years 11 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
ISNN
2004
Springer
14 years 27 days ago
Fuzzy-Kernel Learning Vector Quantization
This paper presents an unsupervised fuzzy-kernel learning vector quantization algorithm called FKLVQ. FKLVQ is a batch type of clustering learning network by fusing the batch learn...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
ICMCS
2006
IEEE
131views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Self-Supervised Learning for Robust Video Indexing
The performance of video analysis and indexing algorithms strongly depends on the type, content and recording characteristics of the analyzed video. Current video indexing approac...
Ralph Ewerth, Bernd Freisleben