: Online meetings are increasingly popular in support of technology-enhanced learning collaboration. When these virtual meetings are recorded and shared in the host community and b...
Peter J. Scott, Linda J. Castaneda, Kevin Quick, J...
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
In this paper, we address the problem of lifelong map learning in static environments with mobile robots using the graph-based formulation of the simultaneous localization and mapp...
Henrik Kretzschmar, Giorgio Grisetti, Cyrill Stach...
The rise of convex programming has changed the face of many research fields in recent years, machine learning being one of the ones that benefitted the most. A very recent develop...
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...