This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action gra...
In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query proce...
Engin Demir, Cevdet Aykanat, Berkant Barla Cambazo...
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
The DAG-based task graph model has been found effective in scheduling for performance prediction and optimization of parallel applications. However the scheduling complexity and s...
Graph drawing and visualization represent structural information ams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). E-Spring alg...