Abstract. We address the problem of having insufficient labels in an interactive image segmentation framework, for which most current methods would fail without further user inter...
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...
This paper addresses the problem of estimating dense correspondence between arbitrary frames from captured sequences of shape and appearance for surfaces undergoing free-form defo...
We measure the effects of a weak language model, estimated from as little as 100k words of text, on unsupervised acoustic model training and then explore the best method of using ...
We show that the number of vertices of a given degree k in several kinds of series-parallel labelled graphs of size n satisfy a central limit theorem with mean and variance proport...