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Graph clustering is about identifying clusters of closely connected nodes, and is a fundamental technique of data analysis with many applications including community detection, VLSI network partitioning, collaborative filtering, and many others. In order to improve the scalability of existing graph ...

We propose a unified framework for making a wide range of PCA-like algorithms – including the standard PCA, sparse PCA and non-negative sparse PCA, etc. – robust when facing a constant fraction of arbitrarily corrupted outliers. Our theoretic analysis establishes solid performance guarantees of the ...

This paper considers estimating the leading k principal components with at most s non-zero attributes from p-dimensional samples collected sequentially in memory limited environments. We develop and analyze two memory and computational efficient algorithms called streaming sparse PCA and streaming s ...

Timber-concrete composite (TCC) structures offer higher stiffness and loading capacity compared to pure timber structures with similar dimensions. A more rigid adhesive interface between concrete and timber offers advantages over conventional connections (e.g., mechanical fasteners and notches) by e ...