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 ...
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Signature-based tools such as network intrusion detection systems are widely used to protect critical systems. Automatic signature generation techniques are needed to enable these...
David Brumley, Hao Wang, Somesh Jha, Dawn Xiaodong...
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...