{"id":2712,"date":"2021-03-28T10:54:27","date_gmt":"2021-03-28T10:54:27","guid":{"rendered":"https:\/\/aims-cameroon.org\/?page_id=2712"},"modified":"2025-05-05T06:21:31","modified_gmt":"2025-05-05T06:21:31","slug":"colloquiums","status":"publish","type":"page","link":"https:\/\/aims-cameroon.org\/fr\/colloquiums\/","title":{"rendered":"COLLOQUES"},"content":{"rendered":"
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Past and Forthcoming Colloquiums\/Workshops<\/strong><\/h1>\n\n\n\n

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Forthcoming Workshop <\/p>\n\n\n\n

AIMS -Cameroon Mathematics and its Applications Meeting (ACMAM) Holds in January 2022<\/strong><\/p>\n\n\n\n

AIMS Cameroon Research Center will organize the maiden edition of its annual scientific event named AIMS-Cameroon Mathematics and its Applications Meeting (ACMAM) from the 12e<\/sup> to the 14e<\/sup> of January, 2022. Lectures take place at the AIMS Cameroon Research Center in Limbe South West Region.<\/p>\n\n\n\n

The AIMS-Cameroon Mathematics and its Applications Meeting (ACMAM) is an initiative to introduce students and early-career researchers to the current trends in Mathematics and its application in Data sciences as well as to create a strong networking environment among academia, industry, and the national laboratories.  This hybrid (face-to-face and online) workshop will be held annually under the title \u201cAIMS-Cameroon Mathematics and its Applications Meeting\u201d (ACMAM) and will see three distinguished speakers give lectures on their research topics.<\/p>\n\n\n

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The focus of the first ACMAM will be on Fundamental Sciences (Mathematics) and its applications to Data Sciences.<\/strong> Researchers from all Mathematics and its Applications areas will be encouraged to participate.

The meeting will comprise mini-courses targeted toward students and early career researchers as well as Public Lectures. There will be other talks and contributions by guest speakers.<\/p>\n\n\n\n

DESCRIPTION<\/strong><\/p>\n\n\n\n

This workshop will introduce students and early-career researchers to the current trends in Mathematics ( Optimization, Optimal transport, PDEs, Calculus of variations, Mean Field Games, and Optimal control) and its Applications, specifically to the fields of Data Sciences (Machine learning, Neural Network etc.), and will lay out various research interests in the field. It also aimed to create a strong networking environment among academia, industry, and national laboratories.<\/p>\n\n\n\n

The extensive successful use of machine learning, Digital twin, Deep learning, Neural networks in communications and information theory, and Climate Sciences in recent years has been remarkable. However, from a mathematical viewpoint, an adequate theoretical understanding of its primary governing principles is still missing in many situations.<\/p>\n\n\n\n

For example, a new continuous viewpoint of artificial neural networks has recently risen, intending to enlighten computing systems\u2019 understanding. As noticed by Fernandez Real and Alessio Figalli in their survey (https:\/\/sma.epfl.ch\/~xafernan\/Documents\/Fernandez-Real_Figalli_Flows_Survey.pdf <\/a>), this theoretical approach has already been developed and shown noticeable and consists in viewing the gradient descent used to optimize parameters in a neural network as a gradient flow in the Wasserstein distance for their empirical measure.<\/p>\n\n\n\n

Most of this study has been conducted from a modeling and numerical point of view. There are still many open questions that are also interesting from a purely theoretical perspective.  In this framework, new mathematical problems and PDE systems have arisen, which have not yet been fully adopted by the mathematical community.<\/p>\n\n\n\n

The Workshop (meeting) aims to discuss this relation, focusing on the associated theoretical aspects appealing to the mathematical community, raising awareness to young researchers, Ph.D. and Masters\u2019s students, and providing a list of interesting open problems related to industry and flourishing local companies.<\/p>\n\n\n\n

However, mathematical theory supporting the most work in Machine learning is missing, and mathematicians are starting to consider this challenging problem of significant importance. The Workshop aims to introduce participants to some of the mathematical foundations of data science in general and Machine Learning in particular. By the end of this annual meeting, participants would be sufficiently armed with the mathematical tools and techniques to potentially undertake theoretical research in Mathematics and its applications in Machine Learning.<\/p>\n\n\n\n

Target Audience
<\/strong>Researchers, Postdocs, Ph.D., and Master\u2019s students.<\/p>\n\n\n\n

Keynote Speakers<\/h3>\n\n\n\n