In the realm of tensor optimization, the low-rank Tucker decomposition is crucial for reducing
the number of parameters and for saving storage. We explore the geometry of Tucker tensor …

Low-rank tensors appear to be prosperous in many applications. However, the sets of
bounded-rank tensors are non-smooth and non-convex algebraic varieties, rendering the …