Spatial Link Prediction with Spatial and Semantic Embeddings

Many applications in automated auditing and the analysis and consistency check of financial documents can be formulated in part as the subset sum problem: Given a set of numbers and a target sum, find the subset of numbers that sums up to the target. The problem is NP-hard and classical solving algorithms are therefore not practical to use in many real applications.We tackle the problem as a QUBO (quadratic unconstrained binary optimization) problem and show how gradient descent on Hopfield Networks reliably finds solutions for both artificial and real data. We outline how this algorithm can be applied by adiabatic quantum computers (quantum annealers) and specialized hardware (field programmable gate arrays) for digital annealing and run experiments on quantum annealing hardware.

  • Published in:
    International Semantic Web Conference
  • Type:
    Inproceedings
  • Authors:
    Mann, Genivika; Dsouza, Alishiba; Yu, Ran; Demidova, Elena
  • Year:
    2023

Citation information

Mann, Genivika; Dsouza, Alishiba; Yu, Ran; Demidova, Elena: Spatial Link Prediction with Spatial and Semantic Embeddings, International Semantic Web Conference, 2023, November, Mann.etal.2023a,

Associated Lamarr Researchers

lamarr institute person demidova elena e1663924269458 - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Elena Demidova

Principal Investigator Hybrid ML to the profile