Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
3D echocardiography is one of the emerging real-time imaging modalities that is increasingly used in clinical practice to assess cardiac function. It provides for evaluation a mor...
Resource Description Framework (RDF) is a general description technology that can be applied to many application domains. Redland is a software library for RDF which implements a ...