In this paper, we model Probabilistic Packet Marking (PPM) schemes for IP traceback as an identification problem of a large number of markers. Each potential marker is associated ...
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
—Wireless Sensor Networks (WSNs) require robustness against channel induced errors while retransmission based schemes prove too costly for energy constrained sensor nodes. Channe...
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
The multiple-instance learning (MIL) model has been very successful in application areas such as drug discovery and content-based imageretrieval. Recently, a generalization of thi...
Qingping Tao, Stephen D. Scott, N. V. Vinodchandra...