Original video

  • Eval a polynomical A(x) at x0 : Horner’s rule
  • Mutlply two polys:
    • Closed form at O(n^2) naively -> O(nlogn) possible
    • Equivalent to convolution of vectors A * reverse(B) - inner products of all possible shifts
  • Poly representations:
    • Samples for n points with all distince xs.
      • Convert between this and coefficient form in O(nlogn)
      • Sampling n points takes O(n^2) in total
    • A sequence of n roots
  • Eval A(x) for x in X: D&C by even/odd i
    • A(x) = A_even(x^2) + x * A_odd(x^2)
    • Derive the recursion and cost => draw the recursion tree and we see it is still n^2
    • Square a number on the unit circle on the complex plane
  • FFT is the d&c algo for DFT (coefficent to sample form)
    • Fast poly multiplicatin: FFT(A) * FFA(B) and then do inverse FFT
  • Similar techique