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Variational Learning on Aggregate Outputs with Gaussian Processes [article]

Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim CD Lucas, Seth Flaxman, Katherine Battle, Kenji Fukumizu
2018 arXiv   pre-print
We consider an approach to this problem based on variational learning with a model of output aggregation and Gaussian processes, where aggregation leads to intractability of the standard evidence lower  ...  We develop a framework which extends to several types of likelihoods, including the Poisson model for aggregated count data.  ...  Acknowledgement We thank Kaspar Martens for useful discussions, and Dougal Sutherland for providing the code base in which this work was based on.  ... 
arXiv:1805.08463v1 fatcat:p6f36i2ipjdvffnp75yxtaa3om

Contributions of context-aided multi-modal perception systems for detection and tracking of moving objects

Egor Sattarov
unpublished
Algorithm 1: Model Training: Overview over the two-stage model training procedure consisting of learning distributions with SOMs, and learning multi-sensory conditional probabilities. for t : 1 \rightar  ...  The set of labeled rectangles representing noisy objects Z.  ...  0.419744 " y r e l=" 1 . 2 9 2 8 9 " z r e l=" 0 . 0 8 5 0 0 0 1 " timestamp=" 1 4 6 6 6 0 1 5 1 8 . 0 7 9 7 7 7 0 0 2 " /> </GPS> </ Track> </ T r a c k l e t s> Listing C.1 --Example of an XML-format for  ... 
fatcat:xg4bukowibfhrgjyn7ymk5ekee