Abstract. The network measurement community has proposed multiple machine learning (ML) methods for traffic classification during the last years. Although several research works ha...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
With the rise of photo-sharing websites such as Facebook and Flickr has come dramatic growth in the number of photographs online. Recent research in object recognition has used su...
Yunpeng Li, David J. Crandall, Daniel P. Huttenloc...
We present a taxonomy for local distance functions where most existing algorithms can be regarded as approximations of the geodesic distance defined by a metric tensor. We categor...