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@INPROCEEDINGS{Pasetto:909756,
      author       = {Pasetto, Edoardo and Delilbasic, Amer and Cavallaro,
                      Gabriele and Willsch, Madita and Melgani, Farid and Riedel,
                      Morris and Michielsen, Kristel},
      title        = {{Q}uantum {S}upport {V}ector {R}egression for {B}iophysical
                      {V}ariable {E}stimation in {R}emote {S}ensing},
      publisher    = {IEEE},
      reportid     = {FZJ-2022-03387},
      isbn         = {978-1-6654-2792-0},
      pages        = {4903-4906},
      year         = {2022},
      abstract     = {Regression analysis has a crucial role in many Earth
                      Observation (EO) applications. The increasing availability
                      and recent development of new computing technologies
                      motivate further research to expand the capabilities and
                      enhance the performance of data analysis algorithms. In this
                      paper, the biophysical variable estimation problem is
                      addressed. A novel approach is proposed, which consists in a
                      reformulated Support Vector Regression (SVR) and leverages
                      Quantum Annealing (QA). In particular, the SVR optimization
                      problem is reframed to a Quadratic Unconstrained Binary
                      Optimization (QUBO) problem. The algorithm is then tested on
                      the D-Wave Advantage quantum annealer. The experiments
                      presented in this paper show good results, despite current
                      hardware limitations, suggesting that this approach is
                      viable and has great potential.},
      month         = {Jul},
      date          = {2022-07-17},
      organization  = {IEEE International Geoscience and
                       Remote Sensing Symposium (IGARSS),
                       Kuala Lumpur (Malaysia), 17 Jul 2022 -
                       22 Jul 2022},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / 5112 - Cross-Domain
                      Algorithms, Tools, Methods Labs (ATMLs) and Research Groups
                      (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-HGF)POF4-5112},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      UT           = {WOS:000920916604255},
      doi          = {10.1109/IGARSS46834.2022.9883963},
      url          = {https://juser.fz-juelich.de/record/909756},
}