Speaker
Description
We present new generic and deterministic uniqueness results for block term decompositions (BTD). These uniqueness conditions hold under mild assumptions and apply to more general settings than previously known results. We also present an algebraic algorithm for the computation of BTDs. Our algorithm requires no knowledge of the block sizes appearing in the BTD: these block sizes are recovered from the algorithm. Through numerical simulations, we illustrate that, in contrast to competing optimization-based methods, even in noisy settings our algebraic algorithm can successfully recover an underlying BTD without knowledge of block sizes provided the signal-to-noise ratio is sufficiently high. We observe that the algorithm can significantly improve one's ability to successfully recover a BTD when it is used as an algebraic initialization for leading optimization routines. Moreover, only a few optimization iterations are required to successfully converge to the BTD from the algebraic solution.