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Application of Computational Intelligence Methods

Introduction of modern computational intelligence methods (evolutionary algorithms, machine learning and related fields) and their application to solving of real problems. Basic knowledge of machine learning, neural networks and evolutionary algorithms is required.

Teach advanced methods combining evolutionary algorithms, neural networks, and other computational intelligence methods. Deepen the knowledge from the introductory courses on neural networks, machine learning, data mining and evolutionary algorithms. The seminar will be focused on working with real data and the cooperation of various methods while solving difficult problems from the areas of optimization, learning and modelling.

Additional study resources/papers

Models for Surrogate Modelling

Adversarial Examples

Deep Style:

Fooling Neural Networks:

Neural Machine Translation:

Image Super-Resolution:

Deep reinforcement learning:

AlphaGO:

Generative Adversarial Networks

Model calibration