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FLAIRS
2009
14 years 7 months ago
Constraint-based Approach to Discovery of Inter Module Dependencies in Modular Bayesian Networks
This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functi...
Patrick de Oude, Gregor Pavlin
SIGIR
2004
ACM
15 years 3 months ago
A nonparametric hierarchical bayesian framework for information filtering
Information filtering has made considerable progress in recent years.The predominant approaches are content-based methods and collaborative methods. Researchers have largely conc...
Kai Yu, Volker Tresp, Shipeng Yu
ICML
2009
IEEE
15 years 10 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...
SDM
2011
SIAM
183views Data Mining» more  SDM 2011»
14 years 15 days ago
Nonparametric Bayesian Co-clustering Ensembles
A nonparametric Bayesian approach to co-clustering ensembles is presented. Similar to clustering ensembles, coclustering ensembles combine various base co-clustering results to ob...
Pu Wang, Kathryn B. Laskey, Carlotta Domeniconi, M...
107
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ICML
2007
IEEE
15 years 10 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...