Introduction¶
In this chapter, we study a particular optimization problem known as least squares.
It is a very important problem because:
It is often the first approach used, for example in inverse problems.
It can be derived statistically from a Gaussian noise assumption.
It lays the foundation for many more sophisticated procedures.
Under some conditions, it admits an explicit (closed-form) solution.