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@INPROCEEDINGS{Ai:916766,
      author       = {Ai, Jiaqi},
      title        = {{I}mprove the {P}auli coefficient measurement with {A}ctive
                      {L}earning},
      reportid     = {FZJ-2023-00090},
      year         = {2022},
      abstract     = {We provide an improvement in the process of Active Learning
                      as a concept from machine learning that labels a large
                      amount of data with a small amount of learning material. In
                      this approach, the method is implemented to speed up
                      measuring the Pauli coefficient for the two-qubit gate. The
                      aim of the implementation is to prove the speed up of the
                      measuring process by reducing unwanted interactions.},
      month         = {Nov},
      date          = {2022-11-14},
      organization  = {JUQCA day, Jülich (Germany), 14 Nov
                       2022 - 14 Nov 2022},
      subtyp        = {Invited},
      cin          = {PGI-2},
      cid          = {I:(DE-Juel1)PGI-2-20110106},
      pnm          = {5224 - Quantum Networking (POF4-522)},
      pid          = {G:(DE-HGF)POF4-5224},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/916766},
}