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Abstract BDDC and FETI-DP algorithms are developed for three-dimensional elliptic problems with adaptively enriched coarse components. It is known that these enriched components are necessary in the development of robust preconditioners. To form the adaptive coarse components, carefully designed generalized eigenvalue problems are introduced for each faces and edges, and the coarse components are formed by using eigenvectors with their corresponding eigenvalues larger than a given tolerance T O L. Upper bounds for condition numbers of the preconditioned systems are shown to be C T O L, with the constant C depending only on the maximum number of edges and faces per subdomain, and the maximum number of subdomains sharing an edge. Numerical results are presented to test the robustness of the proposed approach.

Heterogeneity is an unwanted variation when analyzing aggregated datasets from multiple sources. Though different methods have been proposed for heterogeneity adjustment, no systematic theory exists to justify these methods. In this work, we propose a generic framework named ALPHA (short for Adaptive Low-rank Principal Heterogeneity Adjustment) to model, estimate, and adjust heterogeneity from the original data. Once the heterogeneity is adjusted, we are able to remove the batch effects and to enhance the inferential power by aggregating the homogeneous residuals from multiple sources. Under a pervasive assumption that the latent heterogeneity factors simultaneously affect a fraction of observed variables, we provide a rigorous theory to justify the proposed framework. Our framework also allows the incorporation of informative covariates and appeals to the Bless of Dimensionality. As an illustrative

Multivariate public key cryptosystems are being focused on as candidates for post-quantum cryptography. Rainbow is one of the most efficient signature schemes in multivariate public key cryptosystems. The main drawback of Rainbow is that their key size is much larger than that of RSA and ECC. In this paper, we propose an efficient variant of Rainbow that has a shorter secret key (and thus generates signatures faster) than the corresponding original Rainbow. In our scheme, we divide each layer of Rainbow into smaller blocks by using diagonal matrix representations. The size of the smaller blocks can be flexibly selected, and this enables us to carefully choose secure parameters so that our proposed scheme is secure against known attacks such as rank attacks, direct attacks, and UOV attack. We estimate that the secret key size of our proposed scheme with 100-bit security is smaller by about 40% than that of the original Rainbow. In addition, an implementation of our scheme in the C language is seen to generate signature faster by 40%.