Signal processing using over-complete representations has been an active research field in recent years. In this article, we study the following two related problems: (1) given tw...
This paper extends our recent game-theoretic approach [1] to design and embed watermarks in Gaussian signals in the presence of an adversary. The detector solves a binary hypothes...
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn th...
Kian Ming Adam Chai, Christopher K. I. Williams, S...
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...