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‎index.html

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.pc-members {
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margin-top: 20px;
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}
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.organizers-section {
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background-color: #f9f9f9;
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padding: 20px;
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margin-top: 20px;
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border-radius: 8px;
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}
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</style>
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</head>
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<body>
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<header>
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<h1>Workshop on Automated Machine Learning (AutoML)</h1>
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<h1>Workshop on Automated Machine Learning (AutoML) - ECAI 2024</h1>
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</header>
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<section>
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<main>
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<!-- Your existing content remains unchanged -->
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<!-- Workshop description -->
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<div class="workshop-description">
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<h2>Workshop Description:</h2>
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<p>
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As the demand for machine learning applications surges, it becomes evident that the available pool of knowledgeable data scientists cannot
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scale proportionally with the increasing data volumes and diverse application requirements in our digital world. To address this challenge,
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various automated machine learning (AutoML) frameworks have emerged, aiming to bridge the gap in human expertise by automating the construction
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of machine learning pipelines. AutoML research aims to automate the machine learning process progressively, with the objective of making effective
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methods accessible to everyone. Therefore, the workshop is designed for a diverse audience, including core machine learning researchers involved
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in various ML domains related to AutoML, such as neural architecture search, hyperparameter optimization, meta-learning, and explainability
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within the AutoML context. It also caters to domain experts seeking to apply machine learning to novel problem domains.
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scale proportionally with the increasing data volumes and diverse application requirements in our digital world. To address this challenge,
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various automated machine learning (AutoML) frameworks have emerged, aiming to bridge the gap in human expertise by automating the construction
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of machine learning pipelines. AutoML research aims to automate the machine learning process progressively, with the objective of making effective
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methods accessible to everyone. Therefore, the workshop is designed for a diverse audience, including core machine learning researchers involved
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in various ML domains related to AutoML, such as neural architecture search, hyperparameter optimization, meta-learning, and explainability
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within the AutoML context. It also caters to domain experts seeking to apply machine learning to novel problem domains.
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</p>
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<p>&nbsp;</p>
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</p>
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We invite submissions on the topics of:
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<b>We invite submissions on the topics of:</b>
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<ul>
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<li>Model selection, hyper-parameter optimization, and model search</li>
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<li>Neural architecture search</li>
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<li>Hyperparameter agnostic algorithms</li>
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<li>AutoML for neuro-fuzzy systems</li>
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</ul>
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<p>&nbsp;</p>
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<b>Submissions:</b>
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<p>
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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.
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However, there are a number of free tools available. Specifically, you are welcome to try a new tool (https://chairingtool.com) currently under development
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for IJCAI, which as the organizer of an ECAI workshop you can use free of charge and with premium support.
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</p>
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<!-- Format section -->
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<h2>Format:</h2>
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<b>Format:</b>
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<p>
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The workshop will follow the classical format of presentations of peer-reviewed papers followed by
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discussion. The typical duration for the workshop is a full day. We will arrange invited talks
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</p>
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<!-- Attendance section -->
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<h2>Attendance:</h2>
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<b>Attendance:</b>
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<p>
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The workshop is timely and relevant for the data management and machine learning research
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communities due to the rapid growth in machine learning applications in almost every application
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</div>
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<!-- List of potential workshop PC members -->
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<div class="pc-members">
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<h2>List of Potential Workshop PC Members:</h2>
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<h3>List of Potential Workshop Participating Members:</h3>
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<ul>
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<li>Amin Beheshti, Professor, School of Computing, Macquarie University, Sydney, Australia</li>
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<li>Riccardo Tommasini, Associate Professor at the Institute National des Sciences Appliquées (INSA)</li>
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</ul>
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</div>
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<div class="organizers-section">
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<h2>Names, affiliations, and contact details of all workshop organisers:</h2>
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<ul>
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<li>
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Prof. Jerry Chun-Wei Lin<br>
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Faculty of Automatic Control, Electronics and Computer Science, Department of Distributed Systems and IT Devices, Silesian University of Technology, Poland<br>
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<a href="mailto:[email protected]">[email protected]</a>
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</li>
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<li>
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Assoc Prof. Radwa Elshawi<br>
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Institute of Computer Science, Tartu University<br>
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<a href="mailto:[email protected]">[email protected]</a>
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</li>
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<li>
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Assoc Prof Stefania Tomasiello<br>
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Department of Industrial Engineering, Università degli Studi di Salerno<br>
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<a href="mailto:[email protected]">[email protected]</a>
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</li>
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</ul>
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</div>
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</main>
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