Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
This paper presents an approach to multi-sensory and multi-modal fusion in which computer vision information obtained from calibrated cameras is integrated with a large-scale sent...
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
We extend the Bayesian skill rating system TrueSkill to infer entire time series of skills of players by smoothing through time instead of filtering. The skill of each participat...
Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thor...