We consider a point-to-point communication system in which data packets randomly arrive to a finite-length buffer and are subsequently transmitted to a receiver over a timevarying ...
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qi...
Software distributed shared memory (DSM) improves the programmability of message-passing machines and workclusters by providing a shared memory abstract (i.e., a coherent global a...
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Over the past ten years, face detection has been thoroughly studied in computer vision research for its interesting applications. However, all of the state-of-the-art statistical ...