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NIPS
2003
15 years 7 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
ER
2004
Springer
107views Database» more  ER 2004»
15 years 11 months ago
A Scaleless Data Model for Direct and Progressive Spatial Query Processing
A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other si...
Sai Sun, Sham Prasher, Xiaofang Zhou
FLAIRS
2003
15 years 7 months ago
Agent-based Spectral Analysis Automation (SAA) for On-board Science Data Processing
The major objective of the Spectral Analysis Automation (SAA) work is to develop an agent-based system that is capable of filtering spectral analysis data and making the selected ...
Walt Truszkowski, Sidney C. Bailin
ICPR
2008
IEEE
16 years 26 days ago
Improving Gaussian processes classification by spectral data reorganizing
We improve Gaussian processes (GP) classification by reorganizing the (non-stationary and anisotropic) data to better fit to the isotropic GP kernel. First, the data is partitione...
Hang Zhou, David Suter
ICML
2010
IEEE
15 years 7 months ago
The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...