6 citations · 7 across the 3 of their papers we have counts for
3 papers
stat.CO2025
Tensor cross interpolation for global discrete optimization with application to Bayesian network inference
Sergey Dolgov, Dmitry Savostyanov
Global discrete optimization is notoriously difficult due to the lack of gradient information and the curse of dimensionality, making exhaustive search infeasible. Tensor cross app…
stat.CO2024★ 1 cited
Tensor product algorithms for inference of contact network from epidemiological data
Sergey Dolgov, Dmitry Savostyanov
We consider a problem of inferring contact network from nodal states observed during an epidemiological process. In a black--box Bayesian optimisation framework this problem reduce…
math.NA2013★ 6 cited
One-site density matrix renormalization group and alternating minimum energy algorithm
Sergey V. Dolgov, Dmitry V. Savostyanov
Given in the title are two algorithms to compute the extreme eigenstate of a high-dimensional Hermitian matrix using the tensor train (TT) / matrix product states (MPS) representat…