We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
Abstract—This paper considers an uplink time division multiple access (TDMA) cognitive radio network where multiple cognitive radios (secondary users) attempt to access a spect...
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...