Neuro-symbolic Metalearning and AutoML
Workshop co-hosted at ECML/PKDD 2023.
Date: September 18, 2023 (afternoon)
Location: Pending the ECML/PKDD room allocation
Invited Speakers
- Artur d’Avila Garcez, City University of London, UK
- Bernhard Pfahringer, University of Waikato, New Zealand
Organization
General organizers / Program Chairs (ordered by last name)
- Pavel Brazdil, University of Porto, Portugal
- Henry Gouk, University of Edinburgh, Scotland
- Jan N. van Rijn, Leiden University, The Netherlands
- Md Kamruzzaman Sarker, University of Hartford, USA
Call For Papers
This workshop explores different types of meta-knowledge, such as performance summary statistics or pre-trained model weights. One way of acquiring meta-knowledge is by observing learning processes and representing it in such a way that it can be used later to improve future learning processes. AutoML systems typically explore meta-knowledge acquired from a single task, e.g., by modelling the relationship between hyperparameters and model performance. Metalearning systems, on the other hand, normally explore metaknowledge acquired on a collection of machine learning tasks. This can be used not only for selection of the best workflow(s) for the current task, but also for adaptation and fine-tuning of a prior model to the new task. Many current AutoML and metalearning systems exploit both types of meta-knowledge. Neuro-symbolic systems explore the interplay between neural network-based learning and symbol-based learning to get the best of those two types of learning. While doing so, it tries to use the existing knowledge as a concrete symbolic representation or as a transformed version of the symbolic representation suited for the learning algorithm. The goal of this workshop is to explore ways in which ideas can be cross-pollinated between the AutoML/Metalearning and neuro-symbolic learning research communities. This could lead to, e.g., systems with interpretable meta-knowledge, and tighter integration between machine learning workflows and automated reasoning systems.
Main research areas:
- Controlling the learning processes
- Definitions of configuration spaces
- Few-shot learning
- Elaboration of feature hierarchies
- Exploiting hierarchy of features in learning
- Meta-learning
- Conditional meta-learning
- Meta-knowledge transfer
- Transfer learning
- Transfer of prior models
- Transfer of meta-knowledge between systems
- Symbolic vs subsymbolic meta-knowledge
- Neuro-symbolic learning
- Explainable and interpretable meta-learning
- Explainable artificial intelligence
Program Committee
- Shikha Bordia(Verisk Analytics)
- Kemilly Dearo
- Hugo Jair Escalante(INAOE)
- Eibe Frank (University of Waikato)
- Joao Gama (INESC TEC - LIAAD)
- Dagmar Gromann
- Filip Ilievski (USC/ISI)
- Pavel Kordík (Czech Technical University in Prague)
- Lars Kotthoff (University of Wyoming)
- Bo Liu (Auburn University)
- Robin Manhaeve (KU Leuven)
- Bernhard Pfahringer (University of Waikato)
- Peter van der Putten (Leiden University)
- Martin Wistuba (Amazon)
Submission
This workshop hosts two tracks:
- Original paper track: Authors can submit novel papers, that have not been accepted elsewhere. Please format your submission according to the LaTeX Lecture Notes in Computer Science format, maximal 12 pages.
- Poster of already published work: Authors can apply for a poster spot for a paper that has recently (less than 2 years) been published elsewhere. During submission, you send a link to the already published version of the work, and the peer-review will determine whether it is a good match based on the topic.
Submissions go through the Conference Management Tool.
Please use the template suggested by the organisation of ECML/PKDD
Format of the Workshop
The workshop will last a half a day. It will include:
- Invited talks
- Short oral presentations
- Poster session
- Panel discussions on “Neuro-symbolic Metalearning and AutoML”
Proceedings
Accepted papers can decide to opt-in to the formal workshop proceedings of ECML/PKDD 2023. The authors of accepted papers can decide whether they wish to have their full paper included or not. In the latter case, publication of a short abstract would be possible.
Important Dates
- Workshop Paper Submission Deadline: 12 June 2023
- Workshop Paper Author Notification: 17 July 2023
- Camera Ready Deadline: End of July 2023
- Workshop: September 18, 2023 (afternoon)