CCV-QAOA is a new complex-valued continuous-variable variant of QAOA that solves real and complex multivariate optimization problems via a variational framework.
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Theta-regularized Kriging penalizes the theta hyperparameter in Gaussian stochastic processes using Lasso, Ridge, or Elastic-net, yielding higher accuracy and stability than prior penalized Kriging variants on numerical tests and engineering cases.
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A Complex-Valued Continuous-Variable Quantum Approximation Optimization Algorithm (CCV-QAOA)
CCV-QAOA is a new complex-valued continuous-variable variant of QAOA that solves real and complex multivariate optimization problems via a variational framework.
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Theta-regularized Kriging: Modelling and Algorithms
Theta-regularized Kriging penalizes the theta hyperparameter in Gaussian stochastic processes using Lasso, Ridge, or Elastic-net, yielding higher accuracy and stability than prior penalized Kriging variants on numerical tests and engineering cases.