If you've never tried to implement academic papers, I think you'll find reimplementations have a very high failure rate. Some of it is probably due to differen

If you've never tried to implement academic papers, I think you'll find reimplementations have a very high failure rate. Some of it is probably due to different datasets, some of it is due to not disclosing the entire algorithm or crucial implementation choices, and some of it is probably due to the bits in the code where "magic goes here", but those parts don't get published... Crucial tweaks to optimization algorithms, smart choices of initialization for iterative algorithms, etc. eg it's not really like saying L-M really tells a practitioner precisely what you did; it's more of a family of techniques.