Hackaday

Writing An Optimizing Tensor Compiler From Scratch

Not everyone will write their own optimizing compiler from scratch, but those who do sometimes roll into it during the course ...
IEEE

Low Rank Matrix Differential Equations as Deep Kernel Principal Component Analysis

Abstract: The overall goal of the paper is to develop a deep kernel principal component analysis (KPCA) for time-dependent data that are nonlinearly distributed in high dimensions. Instead of ...
IEEE

Matrix Coding Enabled Impact Mitigation Against Primary False Data Injection Attacks in Cyber-Physical Microgrids

Abstract: The impact mitigation against false data injection attacks (FDIAs) has become a prevailing topic in enhancing the cyber resilience of microgrids. In particular, the primary FDIA (PFDIA) ...
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Visualizing high-dimensional data using PCA in Scikit-Learn

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and visualization. Gingrich: Time for 'national conversation' about immigrants living ...