The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
To learn a metric for query?based operations, we combine the concept underlying manifold learning algorithms and the minimum volume ellipsoid metric in a unified algorithm to find...
There is an increasing need for Internet hosts to be able to quickly and efficiently learn the distance, in terms of metrics such as latency or bandwidth, between Internet hosts. ...
Paul Francis, Sugih Jamin, Vern Paxson, Lixia Zhan...
We investigate the properties of a metric between two distributions, the Earth Mover's Distance (EMD), for content-based image retrieval. The EMD is based on the minimal cost ...