Vol-3470
urn:nbn:de:0074-3470-3

Copyright © 2023 for the individual papers by the papers' authors. Copyright © 2023 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@ECML-PKDD 2023
Interactive Adaptive Learning 2023

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 2023)

Torino, Italy, September 22nd, 2023.

Edited by

Mirko Bunse *
Barbara Hammer
Georg Krempl *
Vincent Lemaire
Alaa Tharwat *
Amal Saadallah *

* TU Dortmund University, Lamarr Institute for Machine Learning and Artificial Intelligence, Joseph-von-Fraunhofer-Str. 25, 44227 Dortmund, Germany
** University of Bielefeld, CITEC Center of Excellence, Inspiration 1, 33619 Bielefeld, Germany
*** Utrecht University, Faculty of Science, 3512 JE Utrecht, Netherlands
**** Orange Innovation, 22300 Lannion, France
***** Hochschule Bielefeld, Kurt-Schumacher-Str. 6, 33615 Bielefeld, Germany

Table of Contents

Preface
Summary: There were 11 papers submitted for peer-review to this workshop. Out of these, 8 papers were accepted for this volume, 5 as regular papers and 3 as short papers. In addition, we publish an extended abstract of the tutorial that we give as a part of the workshop program.

Extended Abstracts

Tutorial: Interactive Adaptive Learning 1-8
Mirko Bunse, Georg Krempl, Alaa Tharwat, Amal Saadallah
Challenges for Active Feature Acquisition and Imputation on Data Streams 9-13
Christian Beyer, Maik Büttner, Myra Spiliopoulou
Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning 14-18
Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider, Sarah Oeste-Reiß
Role of Hyperparameters in Deep Active Learning 19-24
Denis Huseljic, Marek Herde, Paul Hahn, Bernhard Sick

Research Papers

Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets 25-45
Zhixin Huang, Yujiang He, Marek Herde, Denis Huseljic, Bernhard Sick
Active Learning for Survival Analysis with Incrementally Disclosed Label Information 46-64
Klest Dedja, Felipe Kenji Nakano, Celine Vens
Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering 65-73
Matthias Aßenmacher, Lukas Rauch, Jann Goschenhofer, Andreas Stephan, Bernd Bischl, Benjamin Roth, Bernhard Sick
Look and You Will Find It: Fairness-Aware Data Collection through Active Learning 74-88
Hilde Weerts, Renée Theunissen, Martijn C. Willemsen
Interpretable Meta-Active Learning for Regression Ensemble Learning 89-103
Ons Saadallah, Zied Rouissi

2023-08-17: submitted by Mirko Bunse, metadata incl. bibliographic data published under Creative Commons CC0
2023-09-01: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|