Workshop Description:
As the demand for machine learning applications surges, it becomes evident that the available pool of knowledgeable data scientists cannot - scale proportionally with the increasing data volumes and diverse application requirements in our digital world. To address this challenge, - various automated machine learning (AutoML) frameworks have emerged, aiming to bridge the gap in human expertise by automating the construction - of machine learning pipelines. AutoML research aims to automate the machine learning process progressively, with the objective of making effective - methods accessible to everyone. Therefore, the workshop is designed for a diverse audience, including core machine learning researchers involved - in various ML domains related to AutoML, such as neural architecture search, hyperparameter optimization, meta-learning, and explainability - within the AutoML context. It also caters to domain experts seeking to apply machine learning to novel problem domains. + scale proportionally with the increasing data volumes and diverse application requirements in our digital world. To address this challenge, + various automated machine learning (AutoML) frameworks have emerged, aiming to bridge the gap in human expertise by automating the construction + of machine learning pipelines. AutoML research aims to automate the machine learning process progressively, with the objective of making effective + methods accessible to everyone. Therefore, the workshop is designed for a diverse audience, including core machine learning researchers involved + in various ML domains related to AutoML, such as neural architecture search, hyperparameter optimization, meta-learning, and explainability + within the AutoML context. It also caters to domain experts seeking to apply machine learning to novel problem domains.
- + +- We invite submissions on the topics of: + + We invite submissions on the topics of:
- Model selection, hyper-parameter optimization, and model search
- Neural architecture search @@ -108,9 +117,20 @@
- Hyperparameter agnostic algorithms
- AutoML for neuro-fuzzy systems
Workshop Description:
+ + Submissions: + +
+ As workshop organizers, you will need to organize your own paper submission process, and ECAI cannot directly support you in that or cover any costs. + However, there are a number of free tools available. Specifically, you are welcome to try a new tool (https://chairingtool.com) currently under development + for IJCAI, which as the organizer of an ECAI workshop you can use free of charge and with premium support. +
-Format:
+ + Format:The workshop will follow the classical format of presentations of peer-reviewed papers followed by discussion. The typical duration for the workshop is a full day. We will arrange invited talks @@ -119,7 +139,7 @@
Format:
-Attendance:
+ Attendance:The workshop is timely and relevant for the data management and machine learning research communities due to the rapid growth in machine learning applications in almost every application @@ -130,7 +150,7 @@
Attendance:
List of Potential Workshop PC Members:
+List of Potential Workshop Participating Members:
- Amin Beheshti, Professor, School of Computing, Macquarie University, Sydney, Australia
- Riccardo Tommasini, Associate Professor at the Institute National des Sciences Appliquées (INSA) @@ -140,6 +160,28 @@
List of Potential Workshop PC Members:
Names, affiliations, and contact details of all workshop organisers:
+-
+
-
+ Prof. Jerry Chun-Wei Lin
+ Faculty of Automatic Control, Electronics and Computer Science, Department of Distributed Systems and IT Devices, Silesian University of Technology, Poland
+ jerry.chun-wei.lin@polsl.pl +
+ -
+ Assoc Prof. Radwa Elshawi
+ Institute of Computer Science, Tartu University
+ radwa.elshawi@ut.ee +
+ -
+ Assoc Prof Stefania Tomasiello
+ Department of Industrial Engineering, Università degli Studi di Salerno
+ stomasiello@unisa.it +
+