2nd International Workshop on

Interactive Adaptive Learning (IAL2018)

Co-Located With The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2018)

10 September 2018 - Dublin (Ireland)

Register

Topic

Science, technology, and commerce increasingly recognise the importance of machine learning approaches for data-intensive, evidence-based decision making.

This is accompanied by increasing numbers of machine learning applications and volumes of data. Nevertheless, the capacities of processing systems or human supervisors or domain experts remain limited in real-world applications. Furthermore, many applications require fast reaction to new situations, which means that first predictive models need to be available even if little data is yet available. Therefore approaches are needed that optimise the whole learning process, including the interaction with human supervisors, processing systems, and data of various kind and at different timings: techniques for estimating the impact of additional resources (e.g. data) on the learning progress; techniques for the active selection of the information processed or queried; techniques for reusing knowledge across time, domains, or tasks, by identifying similarities and adaptation to changes between them; techniques for making use of different types of information, such as labelled or unlabelled data, constraints or domain knowledge. Such techniques are studied for example in the fields of adaptive, active, semi-supervised, and transfer learning. However, this is mostly done in separate lines of research, while combinations thereof in interactive and adaptive machine learning systems that are capable of operating under various constraints, and thereby address the immanent real-world challenges of volume, velocity and variability of data and data mining systems, are rarely reported. Therefore, this workshop aims to bring together researchers and practitioners from these different areas, and to stimulate research in interactive and adaptive machine learning systems as a whole. Thereby, it continues the successful first workshop on Interactive Adaptive Learning at ECML PKDD 2017 in Skopje.

The workshop aims at discussing techniques and approaches for optimising the whole learning process, including the interaction with human supervisors, processing systems, and includes adaptive, active, semi-supervised, and transfer learning techniques, and combinations thereof in interactive and adaptive machine learning systems. Our objective is to bridge the communities researching and developing these techniques and systems in machine learning and data mining. Therefore, we welcome contributions that present a novel problem setting, propose a novel approach, or report experience with the practical deployment of such a system and raise unsolved questions to the research community.

In particular, we welcome contributions that address aspects including, but not limited to:

    Novel Techniques for Active, Semi-Supervised, Transfer Learning
  • methods for big, evolving, or streaming data,
  • methods for recent complex model structures such as deep learning neural networks or recurrent neural networks,
  • methods for interacting with imperfect or multiple oracles, e.g. learning from crowds,
  • methods for incorporating domain knowledge and constraints,
  • methods for timing the interaction and for combining different types of information,
  • online and ensemble methods for evolving models and systems, with specific switching and fusion techniques, and (inter-)active data integration technqiues,
  • Innovative Use and Applications of Active, Semi-Supervised, Transfer Learning
  • for filtering, forgetting, resampling,
  • for active class or feature selection, e.g. from multi-modal data,
  • for detection of change, outliers, frauds, or attacks,
  • new interactive learning protocols and application scenarios, e.g., brain-computer interfaces, crowdsourcing, ...
  • in application in data-intensive science,
  • in applications with real-world deployment,
  • Techniques for Combined Interactive Adaptive Learning
  • methods combining adaptive, active, semi-supervised, or transfer learning techniques,
  • cost-aware methods and methods for estimating the impact of employing additional resources, such as data or processing capacities, on the learning progress,
  • methodologies for the evaluation of such techniques, and comparative studies,
  • methods for automating the control of an interactive adaptive learning process.

Important dates

The following timeline shows the most important dates for the workshop.

  • Submission open

    14 May 2018

    You can submit your contributions via EasyChair.

  • Submission deadline EXTENDED

    9 July 2018 (full papers)
    23 July 2018 (extended abstracts)

  • Notification

    23 July 2018 (full papers)
    30 July 2018 (extended abstracts)

    ECML PKDD offers the early bird registration rate until 31 July 2018.

  • Camera Ready

    6 August 2018

  • Workshop (Half Day)

    10 September 2018

    Co-Located With The The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2018).

Submit your contribution

Submission is now closed.

Full Paper Track

The full paper track covers new innovative contributions in the area of interactive adaptive learning. If you have a new method already evaluated briefly, a new tool to simplify interaction or some new insights the community might benefit from, please submit a regular paper. The page limit is 10 pages (excluding references and supplemental material).

Submission Deadline: 2 July 2018

Extended Abstract Track

The extended abstract track is ideal to discuss new ideas in the area of interactive adaptive learning. We encourage you to submit open challenges in research or industrial applications to initiate a discussion and find colleagues to collaborate with. The page limit is 2 pages (excluding references and supplemental material).

Submission Deadline: 23 July 2018

Open Access

All accepted papers will be published at ceur-ws.org (indexed by e.g. google scholar). You are allowed to share, upload and distribute your paper. Reviews are single-blind.

LNCS Style

The paper must be be written in English and contain author names, affiliations, and email addresses. The paper must be in PDF using the LNCS format. See instructions here.

Presentation

All accepted papers are presented in spotlight talks and/or poster sessions. At least one author of each accepted paper must be registered to the workshop.

Program

This program is still tentative.

Time Program Presenter/Author
14:00 - 14:05 Welcome Organizing Committee
14:05 - 14:20 Introduction
What is Interactive Adaptive Learning?
Daniel Kottke
14:20 - 15:20 Session 1: Presentation of Full Papers
15m On the Labeling Correctness in Computer Vision Datasets Mohammed Al-Rawi
15m Semi-supervised and Active Learning in Video Scene Classification from Statistical Features Tomáš Šabata, Petr Pulc and Martin Holena
15m Open Research Review: A Crowd-powered Model for Dependent Opinions Sujoy Chatterjee
15m Active Stream Learning with an Oracle of Unknown Availability for Sentiment Prediction Elson Serrao and Myra Spiliopoulou
15:20 - 15:40 Spotlights on Poster Session  
3m Human-Technology relations in a machine learning based commuter app Lars Holmberg
3m An Interactive Learning Scenario for Real-time Environmental State Estimation Based on Heterogeneous and Dynamic Sensor Systems Agnes Tegen, Paul Davidsson and Jan Persson
3m Adaptive Selection of Gaussian Process Model for Active Learning in Expensive Optimization Jakub Repický, Zbyněk Pitra and Martin Holena
3m Towards Interactive Feature Selection with human-in-the-loop Maialen Larranaga, Dimitra Gkorou, Thiago Guzella, Alexander Ypma, Faegheh Hasibi and Robert Jan van Wijk
3m Transfer of Knowledge for Surrogate Model Selection in Cost-Aware Optimization Zbyněk Pitra, Jakub Repický and Martin Holena
3m Embodiment Adaptation from Interactive Trajectory Preferences Michael Walton, Ben Migliori and John Reeder
Start Morning Coffee Break
15:40 - 16:30 Poster Session
Extended coffee break including poster session
 
End Morning Coffee Break
16:30 - 17:00 Session 2: Presentation of Full Papers
15m ActivMetal: Algorithm Recommendation with Active Meta Learning Lisheng Sun-Hosoya, Isabelle Guyon and Michele Sebag
15m Alignment-Based Topic Extraction Using Word Embedding Tyler Newman and Paul Anderson
17:00 - 17:40 Hot Topics in IAL
Short ignite talks (including discussion) presenting recent challenges in IAL research.
tba

Accepted Papers

Long Papers:
  • Mohammed Al-Rawi and Dimosthenis Karatzas. On the Labeling Correctness in Computer Vision Datasets
  • Tomáš Šabata, Petr Pulc and Martin Holena. Semi-supervised and Active Learning in Video Scene Classification from Statistical Features
  • Sujoy Chatterjee. Open Research Review: A Crowd-powered Model for Dependent Opinions
  • Elson Serrao and Myra Spiliopoulou. Active Stream Learning with an Oracle of Unknown Availability for Sentiment Prediction
  • Lisheng Sun-Hosoya, Isabelle Guyon and Michele Sebag. ActivMetal: Algorithm Recommendation with Active Meta Learning
  • Tyler Newman and Paul Anderson. Alignment-Based Topic Extraction Using Word Embedding

Extended Abstracts:
  • Lars Holmberg. Human-Technology relations in a machine learning based commuter app
  • Agnes Tegen, Paul Davidsson and Jan Persson. An Interactive Learning Scenario for Real-time Environmental State Estimation Based on Heterogeneous and Dynamic Sensor Systems
  • Jakub Repický, Zbyněk Pitra and Martin Holena. Adaptive Selection of Gaussian Process Model for Active Learning in Expensive Optimization
  • Maialen Larranaga, Dimitra Gkorou, Thiago Guzella, Alexander Ypma, Faegheh Hasibi and Robert Jan van Wijk. Towards Interactive Feature Selection with human-in-the-loop
  • Zbyněk Pitra, Jakub Repický and Martin Holena. Transfer of Knowledge for Surrogate Model Selection in Cost-Aware Optimization
  • Michael Walton, Ben Migliori and John Reeder. Embodiment Adaptation from Interactive Trajectory Preferences

Committee

Organizing Committee:
ial2018 (at) easychair.org

Georg Krempl

georg.krempl (at) ovgu.de
University Magdeburg, Germany

Vincent Lemaire

vincent.lemaire (at) orange.com
Orange Labs, France

Daniel Kottke

daniel.kottke (at) uni-kassel.de
University of Kassel, Germany

Andreas Holzinger

a.holzinger (at) hci-kdd.org
Medical University Graz, Austria

Robi Polikar

polikar (at) rowan.edu
Rowan University, USA

Bernhard Sick

bsick (at) uni-kassel.de
University of Kassel, Germany

Adrian Calma

acalma (at) uni-kassel.de
University of Kassel, Germany

Program Committee (to be completed):

Les Atlas (Univ. Washington)
Alexis Bondu (EDF R+D)
Lisheng Sun-Hosoya (LRI, Univ. Paris Saclay)
Marek Herde (Univ. Kassel)
Edwin Lughofer (Univ. Linz)
Rolf Würtz (Univ. Bochum)
Denis Huseljic (Univ. Kassel)
Luca Longo (Dublin Inst. of Technology)
Freddy Lecue (Accenture Labs)
Jurek Stefanowski (Poznan University)