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NIPS
2004
13 years 6 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, ...
BMCBI
2008
148views more  BMCBI 2008»
13 years 5 months ago
Discovering biclusters in gene expression data based on high-dimensional linear geometries
Background: In DNA microarray experiments, discovering groups of genes that share similar transcriptional characteristics is instrumental in functional annotation, tissue classifi...
Xiangchao Gan, Alan Wee-Chung Liew, Hong Yan
AAAI
2006
13 years 6 months ago
Embedding Heterogeneous Data Using Statistical Models
Embedding algorithms are a method for revealing low dimensional structure in complex data. Most embedding algorithms are designed to handle objects of a single type for which pair...
Amir Globerson, Gal Chechik, Fernando Pereira, Naf...
SIGMOD
2010
ACM
323views Database» more  SIGMOD 2010»
13 years 9 months ago
Boosting spatial pruning: on optimal pruning of MBRs
Fast query processing of complex objects, e.g. spatial or uncertain objects, depends on efficient spatial pruning of the objects’ approximations, which are typically minimum bou...
Tobias Emrich, Hans-Peter Kriegel, Peer Kröge...
IDA
2009
Springer
13 years 2 months ago
Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases
We propose a method for trajectory classification based on trajectory voting in Moving Object Databases (MOD). Trajectory voting is performed based on local trajectory similarity. ...
Costas Panagiotakis, Nikos Pelekis, Ioannis Kopana...