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 develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
The paradox of fuzzy modeling is recognized due to the co-existence of its effectiveness of solving uncertain problems in the real world and the skepticism of its reasonability in ...