In this paper, we investigate the problem of binary classification with a reject option in which one can withhold the decision of classifying an observation at a cost lower than t...
We develop and analyze an algorithm for nonparametric estimation of divergence functionals and the density ratio of two probability distributions. Our method is based on a variati...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
— Recent advances in statistical timing analysis (SSTA) achieve great success in computing arrival times under variations by extending sum and maximum operations to random variab...
— We propose a new family of classification algorithms in the spirit of support vector machines, that builds in non-conservative protection to noise and controls overfitting. O...