Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer ge...
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...