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» Multi-Instance Dimensionality Reduction
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COMPGEOM
2007
ACM
13 years 11 months ago
Embeddings of surfaces, curves, and moving points in euclidean space
In this paper we show that dimensionality reduction (i.e., Johnson-Lindenstrauss lemma) preserves not only the distances between static points, but also between moving points, and...
Pankaj K. Agarwal, Sariel Har-Peled, Hai Yu
NIPS
2004
13 years 9 months ago
Multiple Relational Embedding
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
Roland Memisevic, Geoffrey E. Hinton
IVC
2007
184views more  IVC 2007»
13 years 7 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
SADM
2010
173views more  SADM 2010»
13 years 2 months ago
Data reduction in classification: A simulated annealing based projection method
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
Tian Siva Tian, Rand R. Wilcox, Gareth M. James
ICIC
2009
Springer
14 years 14 days ago
Dimension Reduction Using Semi-Supervised Locally Linear Embedding for Plant Leaf Classification
Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant...
Shanwen Zhang, Kwok-Wing Chau