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» Dirichlet Process Mixtures of Generalized Linear Models
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KDD
2008
ACM
156views Data Mining» more  KDD 2008»
16 years 3 days ago
Unsupervised deduplication using cross-field dependencies
Recent work in deduplication has shown that collective deduplication of different attribute types can improve performance. But although these techniques cluster the attributes col...
Robert Hall, Charles A. Sutton, Andrew McCallum
EMMCVPR
2007
Springer
15 years 5 months ago
Bayesian Order-Adaptive Clustering for Video Segmentation
Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
Peter Orbanz, Samuel Braendle, Joachim M. Buhmann
IJCV
2008
172views more  IJCV 2008»
14 years 11 months ago
Nonparametric Bayesian Image Segmentation
Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model f...
Peter Orbanz, Joachim M. Buhmann
TSP
2011
230views more  TSP 2011»
14 years 6 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
ICASSP
2011
IEEE
14 years 3 months ago
Non-parametric bayesian measurement noise density estimation in non-linear filtering
In this study, we investigate online Bayesian estimation of the measurement noise density of a given state space model using particle filters and Dirichlet process mixtures. Diri...
Emre Özkan, Saikat Saha, Fredrik Gustafsson, ...