Metrics on diagram groups and uniform embeddings in a Hilbert space
نویسندگان
چکیده
منابع مشابه
On the Hilbert Space Embeddings and Metrics on Probability Measures
A Hilbert space embedding for probability measures has recently been proposed (Gretton et al., 2007; Smola et al., 2007), with applications including dimensionality reduction, homogeneity testing and independence testing. This embedding represents any probability measure as a mean element in a reproducing kernel Hilbert space (RKHS). Using this embedding, a pseudometric (let us define it as γk)...
متن کاملHilbert Space Embeddings and Metrics on Probability Measures
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing, and independence testing. This embedding represents any probability measure as a mean element in a reproducing kernel Hilbert space (RKHS). A pseudometric on the space of probability measures can be defined as the distance between distribution...
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Many problems in machine learning and artificial intelligence involve discrete-time partially observable nonlinear dynamical systems. If the observations are discrete, then Hidden Markov Models (HMMs) (Rabiner, 1989) or, in the control setting, Partially Observable Markov Decision Processes (POMDPs) (Sondik, 1971) can be used to represent belief as a discrete distribution over latent states. Pr...
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ژورنال
عنوان ژورنال: Commentarii Mathematici Helvetici
سال: 2006
ISSN: 0010-2571
DOI: 10.4171/cmh/80