Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
In distributed work systems, individual users perform work for other users. A significant challenge in these systems is to provide proper incentives for users to contribute as muc...
Most studies in statistical or machine learning based authorship attribution focus on two or a few authors. This leads to an overestimation of the importance of the features extra...
We present an efficient method for mutual information (MI) computation between images (2D or 3D) for NVIDIA’s ‘compute unified device architecture’ (CUDA) compatible devic...