Publications [#350122] of Rong Ge

Papers Published

1. Frandsen, A; Ge, R, Optimization landscape of Tucker decomposition, Mathematical Programming, vol. 193 no. 2 (June, 2022), pp. 687-712 [doi]
   (last updated on 2026/01/16)

   Abstract:
   Tucker decomposition is a popular technique for many data analysis and machine learning applications. Finding a Tucker decomposition is a nonconvex optimization problem. As the scale of the problems increases, local search algorithms such as stochastic gradient descent have become popular in practice. In this paper, we characterize the optimization landscape of the Tucker decomposition problem. In particular, we show that if the tensor has an exact Tucker decomposition, for a standard nonconvex objective of Tucker decomposition, all local minima are also globally optimal. We also give a local search algorithm that can find an approximate local (and global) optimal solution in polynomial time.