Linear regression is a widely used technique to fit linear models and finds widespread applications across different areas such as machine learning statistics. In most real-world scenarios, however, problems are often ill-posed or the underlying model suffers from overfitting, leading erroneous trivial solutions. This dealt with by adding extra constraints, known regularization. this paper, we ...

Abstract Do you want to know what an anti-chiece Latin square is? Or a non-consecutive toroidal modular We invented ton of new types squares, some inspired by existing Sudoku variations. can’t wait introduce them and answer important questions, such as: do they even exist? If so, under conditions? What are their interesting properties? And how we generate them?