The ability to discover network organization, whether in the form of explicit topology reconstruction or as embeddings that approximate topological distance, is a valuable tool. T...
Brian Eriksson, Paul Barford, Robert Nowak, Mark C...
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
— While robot mapping has seen massive strides , higher level abstractions in map representation are still not widespread. Maps containing semantic concepts such as objects and l...
This paper describes the design and execution of a roboticsthemed AI elective at a small liberal arts institution. An important goal of the course is to spark and nurture students...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...