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UAI
2001
13 years 9 months ago
Improved learning of Bayesian networks
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
Tomás Kocka, Robert Castelo
ICML
2009
IEEE
14 years 8 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge
CHI
2006
ACM
14 years 8 months ago
Quantifying interpersonal influence in face-to-face conversations based on visual attention patterns
A novel measure for automatically quantifying the amount of interpersonal influence present in face-toface conversations is proposed based on the visualattention patterns of the p...
Kazuhiro Otsuka, Junji Yamato, Yoshinao Takemae, H...
ICA
2010
Springer
13 years 8 months ago
Non-negative Hidden Markov Modeling of Audio with Application to Source Separation
Abstract. In recent years, there has been a great deal of work in modeling audio using non-negative matrix factorization and its probabilistic counterparts as they yield rich model...
Gautham J. Mysore, Paris Smaragdis, Bhiksha Raj