Institute of Information Theory and Automation

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Projects

Dept.: MTR Duration: 2019 - 2021
The aim of the project is to apply the methods of polyhedral geometry to solve mathematical problems with motivation in statistics and artificial intelligence. The goals concern several areas: statistical learning graphical models of conditional independence structure, theory for application of graphical models, supermodular functions, secret sharing schemes, theory of cooperative games and...
Dept.: MTR Duration: 2013 - 2015
The application of algebraic and geometric methods is one of the present trends in modern statistics. The aim of the project is to apply the methods of combinatorial optimization to problems with motivation in statistics and artificial intelligence. The goals are divided into three groups: the goals concerning statistical learning Bayesian network structure and conditional independence, the...
Dept.: MTR Duration: 2004 - 2006
The concept of conditional independence (CI) plays an essential role in the area of decision-making under uncertainty (in artificial intelligence), in particular, in the area of probabilistic reasoning. The aim of the project is to try to solve mathematical problems which arise in connection with the methods of computer representation of CI structures and their learning based on data. Procedures...