Abstract As introduced in the previous chapters, complexity of hypergraph computation is relatively high. In practical applications, may not be a small scale, where we often encounter scenario that size very large. Therefore, confronts issues many applications. how to handle large scale data an important task. this chapter, discuss methods for hypergraphs and their Two types are provided data, ...

Abstract High-throughput computational imaging requires efficient processing algorithms to retrieve multi-dimensional and multi-scale information. In phase imaging, retrieval (PR) is required reconstruct both amplitude in complex space from intensity-only measurements. The existing PR suffer the tradeoff among low complexity, robustness measurement noise strong generalization on different modal...

Roughly speaking, let us say that a map between metric spaces is large scale conformal if it maps packings by balls to quasi-balls with limited overlaps. This quasi-isometry invariant notion makes sense for finitely generated groups. Inspired work Benjamini and Schramm, we show under such maps, some kind of dimension increases: exponent volume growth nilpotent groups, the ideal boundary hyperbo...