Monte Carlo Filtering Using Kernel Embedding of Distributions | Zendy

Motonobu Kanagawa | Zendy; Yu Nishiyama | Zendy; Arthur Gretton | Zendy; Kenji Fukumizu | Zendy

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Monte Carlo Filtering Using Kernel Embedding of Distributions

Author(s) -

Motonobu Kanagawa,

Yu Nishiyama,

Arthur Gretton,

Kenji Fukumizu

Publication year - 2014

Publication title -

proceedings of the aaai conference on artificial intelligence

Language(s) - English

Resource type - Journals

eISSN - 2374-3468

pISSN - 2159-5399

DOI - 10.1609/aaai.v28i1.8984

Subject(s) - kernel (algebra) , monte carlo method , kernel embedding of distributions , kernel smoother , embedding , variable kernel density estimation , algorithm , computer science , kernel method , hybrid monte carlo , kernel principal component analysis , particle filter , monte carlo method in statistical physics , reproducing kernel hilbert space , artificial intelligence , mathematics , markov chain monte carlo , radial basis function kernel , hilbert space , kalman filter , mathematical analysis , discrete mathematics , statistics , support vector machine

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