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LOD 2023 : International Conference on Machine Learning, Optimization, and Data Science


When Sep 22, 2023 - Sep 26, 2023
Where Grasmere, Lake District, England – UK
Submission Deadline Apr 10, 2023
Notification Due Jun 10, 2023
Final Version Due Jun 30, 2023
Categories    machine learning   optimization   data science   computer science

Call For Papers

Since 2015, the LOD Conference brings academics, researchers and industrial researchers together in a unique multidisciplinary community to discuss state of the art and latest advances in the integration of machine learning, optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI. Since 2017, LOD adopted the Asilomar AI Principles.

The 9th International Conference on Machine Learning, Optimization, and Data Science (LOD) has established itself as a premier multidisciplinary conference in machine learning, computational optimization, knowledge discovery and data science. It provides an international forum for the presentation of original multidisciplinary research results, and the exchange and dissemination of innovative and practical development experiences.

LOD 2023 will be held in The Wordsworth Hotel & SPA in Grasmere – Lake District, England - UK on September 22 – 26, 2023. The conference will consist of four days of conference sessions. We invite submissions of papers on all topics related to Machine learning, Optimization, Knowledge Discovery and Data Science, including real-world applications for the Conference Post-Proceedings by Springer Nature – Lecture Notes in Computer Science (LNCS).


Gabriel Barth-Maron, DeepMind, London, UK
Talk(s): TBA

Anthony G. Cohn, University of Leeds, UK & The Alan Turing Institute, UK
"Evaluating the Commonsense Reasoning abilities of Foundation Models"

Sven Giesselbach, Fraunhofer Institute - IAIS, Germany
"Foundation Models"
"OpenGPT-X and Application and Practical Training of Large Scale Language Models"

Satellite Events:
International Meeting on Foundation Models
Workshop AI for Medicine
25 Tracks

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