Abstract Interpretable machine learning has become a very active area of research due to the rising popularity algorithms and their inherently challenging interpretability. Most work in this been focused on interpretation single features model. However, for researchers practitioners, it is often equally important quantify importance or visualize effect feature groups. To address gap, we provide...

3D human pose estimation by grouping body joints according to anatomical relationship is currently a popular and effective method. For grouped estimation, fusing features of different groups together effectively the key step ensure integrity whole prediction. However, existing methods for feature fusion between require large number network parameters, thus are often computational expensive. In ...

background: to conduct a systematic review and meta-analysis on controlled treatment trials of meta-cognitive therapy for anxiety disorders. materials and methods: studies were included if they employed controlled methodology and treated people above 18 years with anxiety disorders. case studies (with less than 4 cases) and single case designed studies were excluded. a comprehensive literature ...

Identification of objects in a scene may be influenced by functional relations among those objects. In this study, observers indicated whether a target object matched a label. Each target was presented with a distractor object, and these were sometimes arranged to interact (as if being used together) and sometimes not to interact. When the distractor was semantically related to the label, ident...

Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model is one of such models, which parametrizes the value of each item by a real valued preference parameter. In this paper, the Plackett-Luce model is generalized to cope with the grouped ranking observations such as movie...