Model selection in unsupervised learning is a hard problem. In this paper a simple selection criterion for hyperparameters in one-class classifiers (OCCs) is proposed. It makes us...
Object-oriented programming techniques support construction of reusable and extensible code. However, class-based languages have poor support for implementing type-orthogonal beha...
This paper presents the use of probabilistic class-based lexica for disambiguation in targetword selection. Our method employs minimal but precise contextual information for disam...
Usually, performance of classifiers is evaluated on real-world problems that mainly belong to public repositories. However, we ignore the inherent properties of these data and how...
This paper provides a unified framework for improving PRF (pseudorandom function) advantages of several popular MACs (message authentication codes) based on a blockcipher modeled a...