Metric learning is a fundamental problem in computer vision. Different features and algorithms may tackle a problem from different angles, and thus often provide complementary inf...
Bo Wang, Jiayan Jiang, Wei Wang 0028, Zhi-Hua Zhou...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
Abstract We present an extensible encoding of object-oriented data models into higherorder logic (HOL). Our encoding is supported by a datatype package that leverages the use of th...
In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new...
We adapt the classic cusum change-point detection algorithm for applications to data network monitoring where various and numerous performance and reliability metrics are availabl...