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Submitted keynotes abstracts are listed below.

CES

Visualisation and crowdsourcing tools for quantitative studies

Data-driven environmental sustainability should consider not just getting more data, but smarter representation of data. Today's...

CES

Graph-representation and learning framework for Smart Cities big data analytics

Given the increased dynamism and complexity of modern world, researchers struggle to cope to exploit as much as possible...

XAI

Machine Learning Enabled Transparent Manufacturing

Benefiting from the advancement of information and communication technology, more and more data related to product manufacturing...

XAI

Explainable AI in process of complexity reduction of DL models and in boosting theirs performance

The performance of AI systems based on deep learning models is exceeding the human level on an increasing number of tasks like...

XAI

Explaining Visual Classification using Attributes

The performance of deep Convolutional Neural Networks (CNN) has been reaching or even exceeding the human level on large number of...

XAI

Causal-AI: Explainability of AI Models through Cause and Effect Reasoning

Interpretability of artificial intelligence (AI) models is one of the most discussed topics in contemporary AI research (Holm...

CES

Scalable Constraint-based Optimisation

Declarative methods for combinatorial optimisation (such as modeling as a CSP) can form the basis of highly scalable solvers...

XAI

The Need to Empirically Evaluate Explanation Quality

Organisations face growing legal and social responsibilities to be able to explain decisions they have made using autonomous...

XAI

Explanation of Smart 5G Network Intrusion Detection using Attack Trees

Successful Intrusion Detection systems heavily rely on machine learning to detect anomaly. However, particularly in 5G networks...

XAI

Explainable artificial intelligence for physical and technical systems

Physical and technical systems are peculiar for machine learning. The solution of a variety of engineering problems necessitates...

XAI

From explaining models to explaining decisions and systems

Explainability has been investigated in several ways in the field of machine learning: there are more interpretable models (e.g...

XAI

On Combing Deep-Learning and Classical Control Theoretic Approaches

End to end deep learning of control policies have gathered much attention in recent times. Their attractiveness stems from the...

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