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AAAI
2006
13 years 9 months ago
A Manifold Regularization Approach to Calibration Reduction for Sensor-Network Based Tracking
The ability to accurately detect the location of a mobile node in a sensor network is important for many artificial intelligence (AI) tasks that range from robotics to context-awa...
Jeffrey Junfeng Pan, Qiang Yang, Hong Chang, Dit-Y...
NIPS
2004
13 years 9 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, ...
ICDM
2006
IEEE
110views Data Mining» more  ICDM 2006»
14 years 1 months ago
Manifold Clustering of Shapes
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...
Dragomir Yankov, Eamonn J. Keogh
NIPS
2007
13 years 9 months ago
Learning the structure of manifolds using random projections
We present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data.
Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul ...
WSOM
2009
Springer
14 years 2 months ago
Towards Semi-supervised Manifold Learning: UKR with Structural Hints
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...