For less half-baked and more polished
exposition, check out my
blog posts.
Because not all posts are publication-worthy. Not all ideas are fully baked, not all words are written, yet all trash should be put on the internet.
Mathematical Programming
Optimization Constrained Optimization Optimization is usually bounded. There is a taxonomy of that differ by:
type of objective linear non-linear quadratic type of constraints hard soft (optional with penalty) equality inequality number of variables and constraints Solving method slack variables (convert inequality to equality) penalty method with constraints optimal solution or approximation (global or local extrema) convexity differentiability Note that there are similarities and this grouping need not be mutually exclusive
Learning AI in ten years
I recently stumbled upon an incredible functional computer science curriculum [1], and saw the value in documenting my progress. In this ever-growing, on-the-fly, and infinite game article, I’ll give my roadmap of what I’m going through, went through, what worked for me, what didn’t, and hopefully encourage some others who are captivated by artificial intelligence, but have been intimidated by the technical barrier to entry.