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» Gaussian Process Models of Spatial Aggregation Algorithms
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IJCAI
2003
13 years 6 months ago
Gaussian Process Models of Spatial Aggregation Algorithms
Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and p...
Naren Ramakrishnan, Christopher Bailey-Kellogg
ICDM
2009
IEEE
207views Data Mining» more  ICDM 2009»
13 years 2 months ago
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and s...
Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh
ICML
2003
IEEE
14 years 5 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
JMLR
2008
159views more  JMLR 2008»
13 years 4 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
ICIP
2010
IEEE
13 years 2 months ago
Gaussian mixture models for spots in microscopy using a new split/merge em algorithm
In confocal microscopy imaging, target objects are labeled with fluorescent markers in the living specimen, and usually appear as spots in the observed images. Spot detection and ...
Kangyu Pan, Anil C. Kokaram, Jens Hillebrand, Mani...