The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Most conventional SFS (shape from shading) algorithms have been developed under the assumption of orthographic projection. However, the assumption is not valid when an object is no...
Kyoung Mu Lee (Seoul National University), C.-C. J...
—In this paper, we consider joint optimization of end-to-end data transmission and resource allocation for Wireless-Infrastructured Distributed Cellular Networks (WIDCNs), where ...
Lei You, Ping Wu, Mei Song, Junde Song, Yong Zhang
— This paper addresses the challenge of forming appropriate heterogeneous robot teams to solve tightly-coupled, potentially multi-robot tasks, in which the robot capabilities may...
Lynne E. Parker, Christopher M. Reardon, Heeten Ch...
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...