Guide to Linear Algebra With the Eigen C++ Library
Talkat CppCon 2024 · on Thursday, 2024-09-19· at 16:45· Cottonwood 8/9, 6700 North Gaylord Rockies Boulevard·
summary
Slides and code show concrete, runnable things: Eigen library (header‑only, expression templates) used for matrix math, QR least‑squares (Householder) to solve a 30×4 regression, and LLT/Cholesky to get a covariance square root; SVD has Jacobi and BDC variants. Interop with the upcoming P1673 / std::mdspan is demonstrated via an Eigen::Map view, including the row‑ vs column‑major gotcha. A portfolio example computes σΩ ≈ 0.02 which the talk maps to ≈0.7 annualized.
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chapters (10)
- 0:00Introduction and history
- 3:01Linear algebra landscape
- 5:03Open-source libraries
- 7:08C++26 linear algebra features
- 11:34Eigen library fundamentals
- 18:56Eigen programming examples
- 28:21Matrix decompositions
- 32:12Applied regression example
- 38:50Integrating Eigen and stdBLAS
- 47:27Summary and conclusions
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