Lecture 33 CSE 331 Nov 15, 2013.

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Lecture 33 CSE 331 Nov 15, 2013

HW 8 due today Place Q1, Q2 and Q3 in separate piles I will not accept HWs after 1:15pm DO NOT FORGET TO WRITE DOWN YOUR SOURCES

Related HW stuff HW 9 has been posted on piazza Solutions to HW 8 at the END of the lecture Can pick up graded HW 7 from Monday

Closest pairs of points Input: n 2-D points P = {p1,…,pn}; pi=(xi,yi) d(pi,pj) = ( (xi-xj)2+(yi-yj)2)1/2 Output: Points p and q that are closest

Dividing up P Q R First n/2 points according to the x-coord

Recursively find closest pairs Q R δ = min (blue, green)

An easy case R > δ Q All “crossing” pairs have distance > δ δ = min (blue, green)

Life is not so easy though Q R δ = min (blue, green)

Life is not so easy though δ Q R > δ > δ > δ δ = min (blue, green)

All we have to do now δ R Q S Figure if a pair in S has distance < δ S δ = min (blue, green)

Rest of today’s agenda Prove the Kickass Property Lemma

HW 8 due today Place Q1, Q2 and Q3 in separate piles I will not accept HWs after 1:15pm DO NOT FORGET TO WRITE DOWN YOUR SOURCES

Three general techniques High level view of CSE 331 Problem Statement Problem Definition Three general techniques Algorithm “Implementation” Data Structures Analysis Correctness+Runtime Analysis

Greedy Algorithms Natural algorithms Reduced exponential running time to polynomial

Divide and Conquer Recursive algorithmic paradigm Reduced large polynomial time to smaller polynomial time

A new algorithmic technique Dynamic Programming

Dynamic programming vs. Divide & Conquer

Same same because Both design recursive algorithms

Different because Dynamic programming is smarter about solving recursive sub-problems

Using Memory to be smarter Pow (a,n) // n is even and ≥ 2 return t * t t= Pow(a,n/2) Pow (a,n) // n is even and ≥ 2 return Pow(a,n/2) * Pow(a, n/2) O(n) as we recompute! O(log n) as we compute only once

End of Semester blues Can only do one thing at any day: what is the optimal schedule to obtain maximum value? Write up a term paper (30) (3) (2) (5) (10) Party! Exam study 331 HW Project Monday Tuesday Wednesday Thursday Friday

Previous Greedy algorithm Order by end time and pick jobs greedily Greedy value = 5+2+3= 10 Write up a term paper (10) OPT = 30 Party! (2) Exam study (5) 331 HW (3) Project (30) Monday Tuesday Wednesday Thursday Friday

Today’s agenda Formal definition of the problem Start designing a recursive algorithm for the problem