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Machine learning has become an essential tool for automatically analyzing imaging data and has already outperformed humans in some image classification tasks. Despite recent progress, there remain enormous challenges when processing large data sets such as image sequences, 3D images, and videos. This mini-symposium presents cutting edge imaging applications of machine learning as well as novel computational approaches for solving large-scale learning problems including advances in stochastic optimization, high-performance computing, and the design of deep neural networks.