About CM2LA
The primary objective of the Center for Mathematical Machine Learning and its Applications (CM2LA) is to address fundamental challenges within the realm of machine learning. Our specific focus revolves around the mathematical mission of quantifying approximation errors inherent in neural networks and machine learning algorithms.
Mathematics forms the bedrock of AI research, as it provides the theoretical framework to elucidate diverse facets of this field. The neural network models we work with are often underpinned by mathematical concepts and principles. At the core of many mathematical disciplines lies the exploration of infinity, limits, and asymptotic properties. These central inquiries are crucial in our pursuit of addressing key questions.
Through in-depth research into practical learning algorithms, which have gained substantial traction in real-world applications, as well as exploration of simpler models for theoretical understanding, we are driven to catalyze groundbreaking advancements in both scientific and technological domains. Furthermore, we are dedicated to pioneering research that transcends disciplinary boundaries, enriching a multitude of fields.
Beyond the academic scope, CM2LA aspires to enhance national competitiveness by nurturing researchers in mathematics and by applying our expertise to solve practical problems in industry and society.