Sum-of-squares optimization

Sum-of-squares optimization is a mathematical approach used primarily in the context of optimizing functions, particularly in the fields of statistics, data fitting, and machine learning. The term generally refers to minimizing the sum of the squares of differences between observed values and values predicted by a model. This method is often employed in regression analysis and linear modeling.