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» Euclidean Embedding of Co-Occurrence Data
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ICCV
2005
IEEE
14 years 8 months ago
Neighborhood Preserving Embedding
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
SIGIR
1999
ACM
13 years 10 months ago
Relevance Feedback Retrieval of Time Series Data
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...
Eamonn J. Keogh, Michael J. Pazzani
ISBI
2008
IEEE
14 years 6 months ago
Support vector machine for data on manifolds: An application to image analysis
The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...
ICPR
2008
IEEE
14 years 13 days ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
AVSS
2009
IEEE
13 years 3 months ago
Landmark Localisation in 3D Face Data
A comparison of several approaches that use graph matching and cascade filtering for landmark localisation in 3D face data is presented. For the first method, we apply the structur...
Marcelo Romero, Nick Pears