Session

DescriptionWith the growing range of machine learning approaches and the availability of large-scale data, performant and scalable algorithmic techniques have become central topics. Nowadays, high-performance computing (HPC) technologies have become essential for modern large-scale machine learning applications. The convergence of HPC and machine learning has shown compelling success across many application fields. With that said, real-world applications are rife with inherent challenges associated with high dimensionality, scarcity of data, and ill-posedness, among many others. This minisymposium will serve as a platform to discuss cutting-edge developments for modern, scalable, and efficient machine learning approaches.