Maximizing Vocabulary Coverage with Books: A Submodular, NP-Hard Selection Problem
Maximizing vocabulary coverage across multiple books is NP-hard, so use greedy submodular optimization for efficient, high-quality approximations.
Computational Complexity
The study of problem difficulty and resource requirements in computation, including complexity classes like P, NP, and NP-hard, and their implications for algorithm design and tractability.
Reading List
Cooley–Tukey: Turning the DFT into O(N log N) (and Why FFT ≠ DFT)
Cooley–Tukey factorizes and reindexes the DFT to turn O(N^2) work into O(N log N), forming the backbone of practical FFTs while clarifying that FFT = algorithm, DFT = result.