We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
This paper presents a random finite set theoretic formulation for multi-object tracking as perceived by a 3D-LIDAR in a dynamic environment. It is mainly concerned with the joint...
Kwang Wee Lee, Bharath Kalyan, W. Sardha Wijesoma,...
Density estimation for observational data plays an integral role in a broad spectrum of applications, e.g. statistical data analysis and information-theoretic image registration. ...
— In a wireless sensor network (WSN), each sensor monitors environmental parameters, and reports its readings to a base station, possibly through other nodes. A sensor works in c...