We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
—This paper describes efficient utilization of human time by two means: prioritization of human tasks and maximizing multirobot team size. We propose an efficient scheduling algo...
We introduce Hierarchical Procrustes Matching (HPM), a segment-based shape matching algorithm which avoids problems associated with purely global or local methods and performs wel...
We address the problem of performance and power-efficient thread allocation in a CMP. To that end, based on analytical model, we introduce a parameterized performance/power metric ...