Abstract. We develop three new techniques to build on the recent advances in online learning with kernels. First, we show that an exponential speed-up in prediction time per trial ...
Classification is an important data mining problem. Given a training database of records, each tagged with a class label, the goal of classification is to build a concise model ...
Johannes Gehrke, Venkatesh Ganti, Raghu Ramakrishn...
Abstract. Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the ...
Abstract— Priority queues are essential for various network processing applications, including per-flow queueing with Quality-of-Service (QoS) guarantees, management of large fa...
This paper presents an algorithm for recovering the globally optimal 2D human figure detection using a loopy graph model. This is computationally challenging because the time comp...