| Vol-2444 urn:nbn:de:0074-2444-4 Copyright © 2019 for the individual papers by the papers' authors. Copyright © 2019 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# IAL 2019
Interactive Adaptive Learning

### Proceedings of the Workshop on Interactive Adaptive Learning
co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2019)

### Würzburg, Germany, September 16th, 2019.

Edited by

### Daniel Kottke *
Georg Krempl **
Vincent Lemaire ***
Andreas Holzinger ****
Adrian Calma *****

* University of Kassel, Faculty of Electrical Engineering and Computer Science, 34121 Kassel, Germany
** Utrecht University, Faculty of Science, 3512 JE Utrecht, Netherlands
*** Orange Labs, 22300 Lannion, France
**** Graz University of Technology, Institute of Interactive Systems & Data Science, 8010 Graz, Austria
***** Vencortex, 34127 Kassel, Germany

## Table of Contents

- Front Matter
- Preface
- Table of Contents

### Tutorials

- Foundations of Interactive Adaptive Learning 1
  Georg Krempl
- From Interactive Adaptive Learning 2
  Andreas Holzinger

### Invited Talk

- Evaluation of Interactive Machine Learning Systems 3
  Nadia Boukhelifa

### Full Research Papers

- On the Labeling Correctness in Computer Vision Datasets 4-16
  Stefan Teso
- Validating One-Class Active Learning with User Studies － a Prototype and Open Challenges 17-31
  Holger Trittenbach, Adrian Engelhardt, Klemens Böhm
- RAL － Improving Stream-Based Active Learning by Reinforcement Learning 32-47
  Sarah Wassermann Thibaut Cuvelier Pedro Casas
- Knowledge-Based Selection of Gaussian Process Surrogates 48-63
  Zbyněk Pitra, Lukáš Bajer, Martin Holeňa
- Explicit Control of Feature Relevance and Selection Stability Through Pareto Optimality 64-79
  Victor Hamer, Pierre Dupont
- Deep Bayesian Semi-Supervised Active Learning for Sequence Labelling 80-95
  Tomáš Šabata, Juraj Eduard Páll Martin Holeňa

### Short Papers

- Combating Stagnation in Reinforcement Learning Through ’Guided Learning’ with ’Taught-Respone Memory’ 96-103
  Keith Tunstead Joeran Beel
- Towards Active Simulation Data Mining 104-107
  Mirko Bunse, Amal Saadallah, Katharina Morik
- Active Feature Acquistion for Opinion Stream Classiﬁcation under Drift 108-111
  Ranjith Shivakumaraswamy, Christian Beyer, Vishnu Unnikrishnan Eirini Ntoutsi Myra Spiliopoulou

2019-09-04: submitted by Daniel Kottke, metadata incl. bibliographic data published under Creative Commons CC0
2019-09-16: published on CEUR-WS.org |valid HTML5|