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ICML
2010
IEEE
13 years 9 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint
UAI
2001
13 years 10 months ago
Exact Inference in Networks with Discrete Children of Continuous Parents
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Uri Lerner, Eran Segal, Daphne Koller
AIED
2007
Springer
14 years 2 months ago
Relating Machine Estimates of Students' Learning Goals to Learning Outcomes: A DBN Approach
Students’ actions while working with a tuoring system were used to generate estimates of learning goals, specifically, the goal of learning by using multimedia help resources, an...
Carole R. Beal, Lei Qu
NIPS
2000
13 years 10 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
ICASSP
2011
IEEE
13 years 11 days ago
Bayesian topic models for describing computer network behaviors
We consider the use of Bayesian topic models in the analysis of computer network traffic. Our approach utilizes latent Dirichlet allocation and time-varying dynamic latent Dirich...
Christopher Cramer, Lawrence Carin