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Anomaly detection on multivariate key performance indicators (KPIs) is a key procedure for the quality and reliability of large-scale cyber-physical systems (CPSs). Although extensive efforts have ...

This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing kernels in ...

[2] On shrinkage estimation for balanced loss functions. Journal of Multivariate Analysis (2020). [3] Bayes minimax estimation of the multivariate normal mean vector under balanced loss function.

In nonparametric multivariate regression analysis, we seek methods to reduce the dimensionality of the regression function to bypass the difficulty caused by the curse of dimensionality. The original ...

We present the Mathematica package MultiHypExp that allows for the expansion of multivariate hypergeometric functions (MHFs), especially those likely to appear as solutions of multi-loop, multi-scale ...

We compared our new algorithm, called General Value Function Outlier Detection (GVFOD), to existing methods for outlier detection in multivariate data. As GVFOD uses reinforcement learning methods, we ...

Figure 1 Comparison of FcR-related NK cell functional measurements between humans and RMs. Distribution of ADCC (A), % NK-mediated ADCC (B), % NK cells (C), % CD16+ NK cellsof live cells (D), CD16 ...

The graph below shows the total number of publications each year in Shrinkage Estimation and Balanced Loss Functions in Multivariate Normal Distribution.