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The 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA) has accepted our scientific paper on AthenIA

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日期: September 19, 2024
类别: News
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The 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA) has accepted our scientific paper on AthenIA

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We’re proud to announce that the DSAA has accepted our scientific paper, “Magazine supply optimization: A case study”, written by Duong NGUYEN, Ana Ulianovici, Sami Achour, Soline Aubry and Nicolas Chesneau at Ekimetrics.

The 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA) will bring together a wealth of industry professionals on the latest theoretical developments in Data Science and best practices for a wide range of real-world applications.

Our accepted paper presents AthenIA, our innovative and applicable solution to optimize magazine supply to over 20,000 points of sale in France.
AthenIA integrates advanced machine learning techniques with business insights, putting business expertise at its center. Adaptable to market fluctuations, our solution helps significantly reduce the carbon footprint associated with over-supply in publishing.

This more sustainable and responsible operational model showcases our R&D capacity, especially in demand sensing/forecasting and supply optimization. We developed an innovative demand-sensing approach for AthenIA and designed a new group-conformalized quantile regression technique to improve the performance of standard quantile regression. We also introduced a tailored optimization model that maximizes profit while considering different operational constraints, complex cost structures, and business strategies.

DSAA ‘24 accepting our paper on AthenIA is a testament to our operational excellence. It strengthens our position as a leader in data science for sustainable transformation that develops solutions to business challenges and delivers impact at scale for our clients.

We would like to recognize the invaluable contribution of the AthenIA team, including the Product team, DA&E, and data scientists, for their dedication to the development and seamless operation of the solution

Want to know more? Read the scientific article: Magazine Supply Optimization: a Case-study

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