*[AM]: Arnoldi Method *[BCG]: Block Conjugate Gradient *[CG]: Conjugate Gradient *[CSP]: Constraint Satisfaction Problem *[CV]: Coefficient of Variation *[CWS]: Class-wise Shapley *[DUL]: Data Utility Learning *[EKFAC]: Eigenvalue-corrected Kronecker-Factored Approximate Curvature *[GT]: Group Testing *[IF]: Influence Function *[iHVP]: inverse Hessian-vector product *[K-FAC]: Kronecker-Factored Approximate Curvature *[LC]: Least Core *[LOO]: Leave-One-Out *[LiSSA]: Linear-time Stochastic Second-order Algorithm *[MCLC]: Monte Carlo Least Core *[MCS]: Monte Carlo Shapley *[MLP]: Multi-Layer Perceptron *[MLRC]: Machine Learning Reproducibility Challenge *[ML]: Machine Learning *[MSE]: Mean Squared Error *[MSR]: Maximum Sample Reuse *[NLRA]: Nyström Low-Rank Approximation *[OOB]: Out-of-Bag *[PCA]: Principal Component Analysis *[PBCG]: Preconditioned Block Conjugate Gradient *[PCG]: Preconditioned Conjugate Gradient *[ROC]: Receiver Operating Characteristic *[SV]: Shapley Value *[TMCS]: Truncated Monte Carlo Shapley *[WAD]: Weighted Accuracy Drop