本仓库是笔者学习优化理论的实验库。
- Boyd, S., & Vandenberghe, L. (2018). Introduction to applied linear algebra: vectors, matrices, and least squares. Cambridge university press.(如需要此教材参考答案可联系笔者)
- Axler, S. (2015). Linear algebra done right (Vol. 2). New York: Springer.
Vector
- Vector
- Linear functions
- Norm and distance
- Clustering ( k-means, optimization conditions)
- Linear independence
Matrices
- Matrices (Matrix norm)
- Linear equations
- Matrix multiplication
- Matrix inverses
Least squares
- Least squares
- Multi-objective least squares
- Constrained least squares
- Nonlinear least squares
-
EXP1: K-Means聚类之Python实现手写数字图像MNIST分类
-
EXP2: Matlab实现QR 分解 (Gram–Schmidt & Householder)
-
EXP3: Matlab实现最小二乘法优化模型(正规方程 & 梯度下降法)