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.
Maximizing vocabulary coverage across multiple books is NP-hard, so use greedy submodular optimization for efficient, high-quality approximations.
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.