Probabilistic Tensor Trains for Large-scale Linear Problems
Background This project will develop arithmetic’s for Probabilistic Tensor Train Decomposition (Hinrich & Mørup, 2019) and apply it to solving large-scale linear problems which are relevant for a variety of applications, e.g. in quantum computing/physics, machine learning, and finance. First, consider the linear problem, A x = b, where A, x, and b are an N by M matrix, M by 1 vector, and N by 1 vector, respectively. In large-scale linear problems M and N are large numbers that have exponential scaling, e....