We describe a probabilistic approach for supervised learning when we have multiple experts/annotators providing (possibly noisy) labels but no absolute gold standard. The proposed...
Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Anna K...
We present an algorithm based on probabilistic latent component analysis and employ it for relative pitch estimation of multiple instruments in polyphonic music. A multilayered po...
Abstract— In this paper the coverage control for mobile sensor networks is studied. The novelty is to consider an anisotropic sensor model where the performance of the sensor dep...
— Interactions are frequently seen between the robot and the targets being tracked within the robotics community. Modeling the interactions using knowledge of robot cognition imp...
In this work, we focus on an improvement of a multi-script handwritting recognition system using a HMM based classifiers combination. The improvement relies on the use of Dempster-...