Probabilistic modelling of text data in the bagof-words representation has been dominated by directed graphical models such as pLSI, LDA, NMF, and discrete PCA. Recently, state of...
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Abstract. Searching and mining nuclear magnetic resonance (NMR)spectra of naturally occurring substances is an important task to investigate new potentially useful chemical compoun...
Alexander Hinneburg, Andrea Porzel, Karina Wolfram
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
The two parameter Poisson-Dirichlet process is also known as the PitmanYor Process and related to the Chinese Restaurant Process, is a generalisation of the Dirichlet Process, and...