Collaborating Authors

Machine learning for subgroup discovery under treatment effect Machine Learning

In many practical tasks it is needed to estimate an effect of treatment on individual level. For example, in medicine it is essential to determine the patients that would benefit from a certain medicament. In marketing, knowing the persons that are likely to buy a new product would reduce the amount of spam. In this chapter, we review the methods to estimate an individual treatment effect from a randomized trial, i.e., an experiment when a part of individuals receives a new treatment, while the others do not. Finally, it is shown that new efficient methods are needed in this domain.

About Algorithm for Transformation of Logic Functions (ATLF) Artificial Intelligence

In this article the algorithm for transformation of logic functions which are given by truth tables is considered. The suggested algorithm allows the transformation of many-valued logic functions with the required number of variables and can be looked in this sense as universal.

Putin's Instagram influencer circle includes famous hockey star


Ya know, the Russian government's pulled a lot of shit on the United States lately, but I did not expect them to reveal that Russian President Vladimir Putin orchestrated the drafting of Russian star Alexander Ovechkin to the Washington Capitals back in 2004 all so Putin could tap the hockey man to lead a pro-Putin propaganda effort from inside the U.S. capital. Can you prove that's not what happened? The real news is this: Ovechkin really is a Russian star for the Washington Capitals. As you can tell from the photo above, he really does occasionally pal around with Putin. And by posting to Instagram on Thursday, he really did seem to launch some sort of pro-Putin social media movement ahead of the Russian presidential "election" coming up in March.

Design, development and implementation of a tool for construction of declarative functional descriptions of semantic web services based on WSMO methodology Artificial Intelligence

Semantic web services (SWS) are self-contained, self-describing, semantically marked-up software resources that can be published, discovered, composed and executed across the Web in a semi-automatic way. They are a key component of the future Semantic Web, in which networked computer programs become providers and users of information at the same time. This work focuses on developing a full-life-cycle software toolset for creating and maintaining Semantic Web Services (SWSs) based on the Web Service Modelling Ontology (WSMO) framework. A main part of WSMO-based SWS is service capability - a declarative description of Web service functionality. A formal syntax and semantics for such a description is provided by Web Service Modeling Language (WSML), which is based on different logical formalisms, namely, Description Logics, First-Order Logic and Logic Programming. A WSML description of a Web service capability is represented as a set of complex logical expressions (axioms). We develop a specialized user-friendly tool for constructing and editing WSMO-based SWS capabilities. Since the users of this tool are not specialists in first-order logic, a graphical way for constricting and editing axioms is proposed. The designed process for constructing logical expressions is ontology-driven, which abstracts away as much as possible from any concrete syntax of logical language. We propose several mechanisms to guarantees the semantic consistency of the produced logical expressions. The tool is implemented in Java using Eclipse for IDE and GEF (Graphical Editing Framework) for visualization.