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CIRM – Centre International de Rencontres Mathématiques

We plan to dedicate the 2023 – 2025 series of conferences to challenges and emerging topics in the area of mathematical statistics driven by the adventure of artificial intelligence. Tremendous progress has been made in building up powerful machine learning algorithms such as random forests, gradient boosting or neural networks. These models are exceptionally complex and difficult to interpret but offer enormous opportunities in many areas of application going from science, public policies to business. These sophisticated algorithms are often called “black boxes” as they are very hard to analyze. The widespread use of such predictive algorithms raises extremely important questions of replicability, reliability, robustness or privacy protection. The proposed series of conferences is dedicated to new statistical methods built around these black-box algorithms that leverage their power but at the same time guarantee their replicability and reliability. The second conference of the program will highlight recent theoretical advances in inference for high-dimensional statistical models based on the interplay of techniques from mathematical statistics, machine learning and theoretical computer science.

Institute of Mathematical Statistics (IMS)

The objective of ICSDS is to bring together researchers in statistics and data science from academia, industry, and government in a stimulating setting to exchange ideas on the developments of modern statistics, machine learning, and broadly defined theory, methods, and applications in data science. There will be a student paper award competition, in addition to plenary sessions, and invited, contributed and poster sessions. Young researchers are particularly encouraged to participate, as a portion of the invited sessions will be designated for young researchers.

Informations & Wissensmanagement, Big Data Computing,    Wissenschaftliches Rechnen und Datenwissenschaft