A probabilistic kernel method for human mobility prediction with smartphones

A probabilistic kernel method for human mobility prediction with smartphones

Human mobility prediction is an important problem that has a large number of applications, especially in context-aware services. This paper presents a study on location prediction using smartphone data, in which we address modeling and application aspects. Building personalized location prediction models from smartphone data remains a technical challenge due to data sparsity, which comes from t...

Human Mobility Prediction: A Probabilistic Transfer Learning Approach

The Lockwood Analytical Method for Prediction within a Probabilistic Framework

A critical aspect of the role of intelligence, within the context of conflict situations involving national level actors, is the reduction in uncertainty associated with ascertaining information relevant to policy makers. Structured techniques for intelligence analysis seek to reduce this uncertainty by the implementation and use of stepwise methods in which each step within the process is tran...

A Probabilistic Method for Prediction of microRNA-target Interactions

Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interaction of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set up a probabilistic model to explain the binding between a microRNA sequence and the sequence of a putative target. To this en...

A Probabilistic Prediction Method for Object Contour Tracking

In this paper we present an approach for probabilistic contour prediction in an object tracking system. We combine level-set methods for image segmentation with optical flow estimations based on probability distribution functions (pdf’s) calculated at each image position. Unlike most recent level-set methods that consider exclusively the sign of the level-set function to determine an object and...