Monday, 13. June, HG-01A32

In this workshop we will discuss (machine learning) architectures where the human involvement in the design of the model and its data ingestion process allows for both more energy efficient and more interpretable outcomes. Examples of such systems stretch from pure grammatical inference methods and probabilistic programming, where the model (family) is entirely constructed by human hands and only very specific model parameters are learned from data, to various types of interpretable neural network approaches where the specific workings of the output system is much less defined a priori. The goal is to spread knowledge about lesser known approaches to learning from data that use an increased level of human involvement, require less training data, and are tailored to achieve interpretable results in a more efficient way.

Schedule

09:00	09:15	Welcome and introductory information
09:15	10:00	Invited Talk: Prof Ole-Christoffer Granmo The Tsetlin Machine – From Arithmetic to Logic-based AI
10:00	11:30	Paper session 1:
		Azqa Nadeem, Sicco Verwer & Shanchieh Jay Yang: Suffix-based Finite Automata for Learning Explainable Attacker Strategies
		Petter Ericson & Anna Jonsson: Grammatical Inference: Strengths and Weaknesses
		Enrique Valero-Leal, Pedro Larrañaga & Concha Bielza: Extending MAP-independence for Bayesian network explainability
		Marco Virgolin, Eric Medvet, Tanja Alderliesten & Peter A.N. Bosman: Less is More: A Call to Focus on Simpler Modelsin Genetic Programming for Interpretable Machine Learning
11:30	12:30	Panel 1: Transparent models and explaining uncertainty
12:30	14:00	Lunch
14:00	14:45	Invited Talk: Dr. Anil Yaman On the Emergence of Collective Intelligence
14:45	15:45	Paper session 2:
		Leila Methnani, Andreas Antoniades & Andreas Theodorou: The AWKWARD Real-Time Adjustment of Reactive Planning
		Krist Shingjergji, Deniz Iren, Felix Böttger, Corrie Urlings & Roland Klemke: Interpretable Explainability for Face Expression Recognition
		Ronald Siebes, Victor de Boer, Roberto Reda & Roderick van der Weerdt: Learning and Reasoning over Smart Home Knowledge Graphs
15:45	16:45	Unconference/excursion (if the weather permits)
16:45	17:45	Panel 2: Transparency and efficiency in practice

Event Timeslots (3)

Monday, 13. June (Pre-C. Day 1)
9:00 am - 6:00 pm
Full day workshop
admin

HG-01A32
9:00 am - 12:30 pm
09:00-09:15 Welcome and introductory information 09:15-10:00 Invited Talk by Prof. Ole-Christoffer Granmo: The Tsetlin Machine – From Arithmetic to Logic-based AI 10:00-11:30 Paper session 1 11:30-12:30 Panel 1: Transparent models and explaining uncertainty
admin

HG-01A32
2:00 pm - 5:45 pm
14:00-14:45 Invited Talk by Dr. Anil Yaman: On the Emergence of Collective Intelligence 14:45-15:45 Paper session 2 15:45-16:45 Unconference/excursion (if the weather permits) 16:45-17:45 Panel 2: Transparency and efficiency in practice
admin