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» Nonparametric statistical inference for ergodic processes
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SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 7 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
ICML
2009
IEEE
14 years 6 months ago
A stochastic memoizer for sequence data
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Cédric Archambeau, Jan Gasthaus...
ICCV
2009
IEEE
14 years 10 months ago
Bayesian selection of scaling laws for motion modeling in images
Based on scaling laws describing the statistical structure of turbulent motion across scales, we propose a multiscale and non-parametric regularizer for optic-flow estimation. R...
Patrick H´eas, Etienne M´emin, Dominique Heitz, ...
ICASSP
2011
IEEE
12 years 9 months ago
Infinite-state spectrum model for music signal analysis
This paper presents a nonparametric Bayesian extension of nonnegative matrix factorization (NMF) for music signal analysis. Instrument sounds often exhibit non-stationary spectral...
Masahiro Nakano, Jonathan Le Roux, Hirokazu Kameok...
ICASSP
2011
IEEE
12 years 9 months ago
Time-evolving modeling of social networks
A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, specifically the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...