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The Information and Inference Systems Laboratory (LIONS) at EPFL focuses on optimized information extraction from signals or data volumes. Their research is divided into two main areas: information scalable optimization and data acquisition, and learning theory for low-dimensional signal models. LIONS develops mathematical theory and computational methods for information recovery from highly incomplete data, with a goal to create adaptive representations, sampling, and computational methods for high-dimensional data. The lab has been actively involved in various projects related to machine learning, optimization, signal processing, information theory, and statistics, collaborating with organizations like FNSNF, HaslerStiftung, Swiss Data Science Center, Zeiss, and Google. LIONS has also made significant contributions to conferences like ICLR and NeurIPS, with multiple papers accepted each year.