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» Embedding ultrametrics into low-dimensional spaces
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ICPR
2008
IEEE
15 years 10 months ago
Unsupervised image embedding using nonparametric statistics
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
Guobiao Mei, Christian R. Shelton
SODA
2007
ACM
106views Algorithms» more  SODA 2007»
14 years 11 months ago
Embedding metrics into ultrametrics and graphs into spanning trees with constant average distortion
This paper addresses the basic question of how well can a tree approximate distances of a metric space or a graph. Given a graph, the problem of constructing a spanning tree in a ...
Ittai Abraham, Yair Bartal, Ofer Neiman
COMPGEOM
2008
ACM
14 years 11 months ago
Circular partitions with applications to visualization and embeddings
We introduce a hierarchical partitioning scheme of the Euclidean plane, called circular partitions. Such a partition consists of a hierarchy of convex polygons, each having small ...
Krzysztof Onak, Anastasios Sidiropoulos
ICIP
2007
IEEE
15 years 11 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...
CORR
2012
Springer
171views Education» more  CORR 2012»
13 years 5 months ago
Random Feature Maps for Dot Product Kernels
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and...
Purushottam Kar, Harish Karnick