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Mathematical Computation on High-dimensional Data via Array Programming and Parallel Acceleration

Mathematical Computation on High-dimensional Data via Array Programming and Parallel Acceleration

来源:Arxiv_logoArxiv
英文摘要

While deep learning excels in natural image and language processing, its application to high-dimensional data faces computational challenges due to the dimensionality curse. Current large-scale data tools focus on business-oriented descriptive statistics, lacking mathematical statistics support for advanced analysis. We propose a parallel computation architecture based on space completeness, decomposing high-dimensional data into dimension-independent structures for distributed processing. This framework enables seamless integration of data mining and parallel-optimized machine learning methods, supporting scientific computations across diverse data types like medical and natural images within a unified system.

Chen Zhang

计算技术、计算机技术

Chen Zhang.Mathematical Computation on High-dimensional Data via Array Programming and Parallel Acceleration[EB/OL].(2025-06-28)[2025-07-16].https://arxiv.org/abs/2506.22929.点此复制

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