Hans's notebook

RNN vs. Structured Learning

Initializing search

Home
C++
ROS
Linux
Python
其他笔记
工作日志
强化学习、深度学习
数学
机器学习
硬件学习
自动驾驶
英语
路径规划

Hans's notebook

Home
C++
C++
ROS
ROS
Linux
Linux
Python
Python
其他笔记
其他笔记
工作日志
工作日志
- 记录每日工作
- 小车培训
- 2022.11
  2022.11
  - 10.30
- 2022.5
  2022.5
  - 5.8
- 2022.6
  2022.6
  - 6.20
- 2022.7
  2022.7
  - 7.1
- 2022.8
  2022.8
  - 8.20
  - Carsim仿真中的速度抖震问题的解决方法
- 2022.9
  2022.9
  - 9.2
- 2023.6
  2023.6
  - 2023.6.29
- 2023.7
  2023.7
  - 会议记录
- IVCPS会议
  IVCPS会议
  - 第一次会议
  - 第二次会议
强化学习、深度学习
强化学习、深度学习
数学
数学
- Lipschitz连续
- Latex Equations Cheatsheet
- 代数重数与几何重数的关系
- 优化问题
- 其他几何知识
- 刚体运动学
- 判断是否相交
- 协方差矩阵
- 四元数与欧拉角、旋转矩阵的转换
- 排列组合
- 方差与均值的关系
- 正定矩阵与凸优化
- 泰勒展开与jacobi矩阵
- Calculus
  Calculus
- Linear Algebra
  Linear Algebra
  - Summary
  - Ax equal b and the Four Subspaces
    Ax equal b and the Four Subspaces
    
    The Geometry of Linear Equations
    
    An Overview of Linear Algebra
    
    Elimination with Matrices
    
    Multiplication and Inverse Matrices
    
    Factorization into A=LU
    
    Transpose, permutations, spaces R^n
    
    Column Space and Nullspace
    
    Soving Ax = 0: pivot variables, special solutions
    
    Solving Ax = b: row reduced form R
    
    Independence, Basis and Dimension
    
    The Four Fundamental Subspaces
    
    Matrix spaces, Rand 1 and Small World Graphs
    
    Graphs, Networks and Incidence Matrices
  - Least Squares Determinants and Eigenvalues
    Least Squares Determinants and Eigenvalues
    
    Orthogonal vectors and subspaces
    
    Projections onto Subspaces
    
    Projection Matrices and Least Squares
    
    Orthogonal Matrices and Gram-Schmidt
    
    Properties of Determinants
    
    Determinant Formulas and Cofactors
    
    Cramer's Rule, Inverse Matrix, and Volume
    
    Eigenvalues and Eigenvectors
    
    Diagonalization and Powers of A
    
    Differential Equations and e^At
    
    Markov Matrices and Fourier Series
  - Positive Definite Matrices and Applications
    Positive Definite Matrices and Applications
    
    Symmetric Matrices and Positive definiteness
    
    Complex Matrices and Fast Fourier Transform
    
    Positive Definite Matrices and Minima
    
    Similar Matrices and Jordan Form
    
    Singular Value Decomposition(SVD)
    
    Linear Transformations and their Matrices
    
    Change of Basis and Image Compression
    
    Left and Right Inverse; Pseudoinverse
- Probability
  Probability
  - Summary
  - Sample Space and Probability
机器学习
机器学习
- 数学基础
硬件学习
硬件学习
自动驾驶
自动驾驶
英语
英语
- 数字的表示
路径规划
路径规划

RNN vs. Structured Learning

Structured Learning 是传统的机器学习方法：HMM CRF

Structured Perceptron/SVM

RNN是深度学习的方法

Made with Material for MkDocs