1 — Divide & Conquer Optimization
Purpose
[stub: divide-and-conquer-optimization]
Metadata
| Author | Amit Singh |
| Scope | data-structures-algorithms |
Local graph
Related notes
7 — Matrix Exponentiation
Representing a linear recurrence as matrix multiplication to compute the n-th term in O(log n).
8 — Fast Exponentiation
Binary exponentiation for computing a^n (or a^n mod m) in O(log n) instead of O(n).
9 — Randomized Algorithms
Algorithms that use randomness for expected-case guarantees — randomized QuickSelect, Monte Carlo vs. Las Vegas framing.
2 — Convex Hull
Finding the smallest convex polygon enclosing a set of points, via Graham scan or the gift-wrapping algorithm.