We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Random Medium-Access-Control (MAC) algorithms have played an increasingly important role in the development of wired and wireless Local Area Networks (LANs) and yet the performanc...
Charles Bordenave, David McDonald, Alexandre Prout...
Local feature approaches to vision geometry and object recognition are based on selecting and matching sparse sets of visually salient image points, known as `keypoints' or `p...
— Sidewinding is an efficient translation gait used by snakes over flat ground. When implemented on snake robots, it retains its general effectiveness, but becomes unstable on ...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...