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» Adaptive metric dimensionality reduction
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NIPS
2004
13 years 5 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
ICML
2007
IEEE
14 years 4 months ago
A transductive framework of distance metric learning by spectral dimensionality reduction
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
Fuxin Li, Jian Yang, Jue Wang
ICDE
2003
IEEE
193views Database» more  ICDE 2003»
14 years 5 months ago
An Adaptive and Efficient Dimensionality Reduction Algorithm for High-Dimensional Indexing
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
Hui Jin, Beng Chin Ooi, Heng Tao Shen, Cui Yu, Aoy...
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 4 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
ICMLA
2008
13 years 5 months ago
Regularized Minimum Volume Ellipsoid Metric for Query-Based Learning
We are interested in learning an adaptive local metric on a lower dimensional manifold for query
Karim T. Abou-Moustafa, Frank P. Ferrie