This paper studies optimal input excitation design for parametric frequency response estimation. We will focus on least-squares estimation of Finite Impulse Response (FIR) models a...
With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
Parametric and feature-based CAD models can be considered to represent families of similar objects. In current modelling systems, however, the semantics of such families are uncle...
Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model ...
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...