Theoretical Foundation of Deep Learning 2018 Workshop
Deep Learning has been a major driving force in the recent surge of interest in Artificial Intelligence (AI), both in academia and in industry. While deep learning has witnessed tremendous empirical success, the theoretical understanding of deep learning remains an important open research field. Promising ideas on the theoretical foundation of deep learning have emerged. The workshop will provide an avenue for researchers in related fields to review existing work, communicate new results, and seek new research directions. In addition to deep learning, related topics will include the generalization ability of deep learning, regularization schemes, adversarial training, generative models, training neural networks, and optimization (convex and non-convex).