Abstract: Dimension reduction is a critical technology for high-dimensional data processing, where Linear Discriminant Analysis (LDA) and its variants are effective supervised methods. However, LDA ...
The fastest Python implementation of the ForceAtlas2 graph layout algorithm, with Cython optimization for 10-100x speedup. Supports NetworkX, igraph, and raw adjacency matrices. ForceAtlas2 is a force ...
Abstract: In this letter, a novel approach is proposed for digital predistortion (DPD) with direct learning architecture (DLA). Regression of a Volterra behavioral model requires the pseudoinverse of ...
This algorithm refers to the article An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control by Panagiotis Patrinos and Alberto Bemporad. You can read the ...
Accurate P-wave first-motion-polarity (FMP) information can contribute to solving earthquake focal mechanisms, especially for small earthquakes, to which waveform-based methods are generally ...
With high imaging accuracy, high signal-to-noise ratio, and good amplitude balance, least-squares reverse time migration (LSRTM) is an imaging algorithm suitable for deep high-precision oil and gas ...
Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...
Linear algebra is involved in virtually all scientific and engineering disciplines, e.g., physics, statistics, machine learning, and signal processing. Solving matrix equations such as a linear system ...
The commutator direct inversion of the iterative subspace (commutator DIIS or C-DIIS) method developed by Pulay is an efficient and the most widely used scheme in quantum chemistry to accelerate the ...
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