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» Euclidean Embedding of Co-Occurrence Data
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NIPS
2004
13 years 8 months ago
Euclidean Embedding of Co-Occurrence Data
Embedding algorithms search for low dimensional structure in complex data, but most algorithms only handle objects of a single type for which pairwise distances are specified. Thi...
Amir Globerson, Gal Chechik, Fernando C. Pereira, ...
ICPR
2010
IEEE
13 years 5 months ago
Rectifying Non-Euclidean Similarity Data Using Ricci Flow Embedding
Similarity based pattern recognition is concerned with the analysis of patterns that are specified in terms of object dissimilarity or proximity rather than ordinal values. For man...
Weiping Xu, Edwin R. Hancock, Richard C. Wilson
ICML
2008
IEEE
14 years 8 months ago
Topologically-constrained latent variable models
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jo...
ICML
2003
IEEE
14 years 8 months ago
Cross-Entropy Directed Embedding of Network Data
We present a novel approach to embedding data represented by a network into a lowdimensional Euclidean space. Unlike existing methods, the proposed method attempts to minimize an ...
Takeshi Yamada, Kazumi Saito, Naonori Ueda
RECSYS
2010
ACM
13 years 7 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street