Interactions between Control Theory and Machine Learning (InterCoML)
This Action will exploit the deep interconnections between Control Theory (CT) and Machine Learning (ML). It will boost applications of tools from CT to ML and vice versa, and explore the great applicative potential that can be released by combining these two rapidly evolving research areas. In particular, it aims to(i) strengthen the control-theoretical foundations […]
Seminar: Towards secure Artificial Intelligence: Private distributed learning and strategic decision making
Towards secure Artificial Intelligence: Private distributed learning and strategic decision making Artificial intelligence faces security challenges at many levels, such as the exposure of sensitive data, the vulnerability of distributed learning systems, and the need to design robust policies under adversarial uncertainty, to name but a few. In this seminar, I will discuss two approaches […]
Bayesian Methods for Machine Learning
Bayesian Methods for Machine Learning The subject is focused on the practical use of basic Bayesian modelling methods in the dynamically evolving machine learning theory. In particular, it studies the construction of appropriate models providing a description of real phenomena, as well as their subsequent use, e.g., for forecasting future evolution or learning about the […]
Theory of Automatic Control
Theory of Automatic Control The course introduces the design, realization, and implementation of digital controllers in industrial practice. It focuses primarily on theoretical training in the field of digital control of linear dynamic systems in terms of stability, accuracy, and quality of transient processes in a closed control loop. Lecturer: Lenka Kuklišová Pavelková Where: […]
Statistics
Statistics The course introduces elements of mathematical statistics. Topics: descriptive statistics, elements of probability theory, discontinuous and continuous random quantities, probability function, probability density function, point and interval estimates, testing of statistical hypotheses, elements of ANOVA, linear regression, correlation analysis, time series analysis, elements of index analysis. Lecturer: Ladislav Jirsa Where: Department of Statistics and […]
Dynamical Systems
Dynamical Systems The course introduces the fundamentals of general systems theory with a focus on linear time-invariant systems, both continuous and discrete, and the most basic tools for their analysis and synthesis. Lecturer: Lenka Kuklišová Pavelková Where: College of Polytechnics Jihlava
Artificial Intelligence
Artificial Intelligence The course introduces the history of artificial intelligence (AI), the basic principles and algorithms of AI, and their practical applications. The course uses the concept of an intelligent agent. Lecturer: Lenka Kuklišová Pavelková Where: College of Polytechnics Jihlava
Introduction to Principles of Computers
Introduction to Principles of Computers The goal of the subject is to acquaint students with the architecture of current software applications. It provides methods of working with static data structures (array, record, object) and dynamic data structures (pointer, list, file…), the principles of structured oriented programming (SOP) and methods of data searching (value search, lookup […]
Discrete structures
Discrete structures The course introduces the basics of set theory, formal logic, and graph theory and their applications in various areas of computer science. Lecturer: Lenka Kuklišová Pavelková Where: College of Polytechnics Jihlava
BSc/MSc/PhD – Prescriptive theory of distributed decision making under uncertainty
Abstract Real processes result from interactions of relatively independently deciding but mutually interacting parts, modelled predominantly as multi-agent systems. A sufficiently complete, normative and algorithmically implementable theory is still missing, which is dearly paid for by effort and quality when solving specific problems. Preliminary results confirm that such a theory can be created by combining […]