A likelihood formulation for human tracking is presented based upon matching feature statistics on the surface of an articulated 3D body model. A benefit of such a formulation ove...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
We present an objective approach for evaluating probability elicitation methods in probabilistic models. Our method draws on ideas from research on learning Bayesian networks: if ...
There is much empirical evidence about the success of naive Bayesian classification (NBC) in medical applications of attribute-based machine learning. NBC assumes conditional inde...
Aleks Jakulin, Ivan Bratko, Dragica Smrke, Janez D...
In the classic Bayesian restless multi-armed bandit (RMAB) problem, there are N arms, with rewards on all arms evolving at each time as Markov chains with known parameters. A play...
Wenhan Dai, Yi Gai, Bhaskar Krishnamachari, Qing Z...