Lecture 37 CSE 331 Dec 1, 2017.

Slides:



Advertisements
Similar presentations
Single Source Shortest Paths
Advertisements

Lecture 40 CSE 331 Dec 11, Announcements Solutions to HW 10 and graded HW 9 at end of the lecture Review session on Monday: see blog for details.
Lecture 38 CSE 331 Dec 7, The last few days Today: Solutions to HW 9 (end of lecture) Wednesday: Graded HW 9 (?), Sample final, Blog post on the.
Lecture 28 CSE 331 Nov 9, Flu and HW 6 Graded HW 6 at the END of the lecture If you have the flu, please stay home Contact me BEFORE you miss a.
Lecture 40 CSE 331 Dec 8, Finals 3:35-6:05pm KNOX 104 Tue, Dec 14 Blog post on the finals up.
Lecture 38 CSE 331 Dec 3, A new grading proposal Towards your final score in the course MAX ( mid-term as 25%+ finals as 40%, finals as 65%) .
Lecture 39 CSE 331 Dec 6, On Friday, Dec 10 hours-a-thon Atri: 2:00-3:30 (Bell 123) Jeff: 4:00-5:00 (Bell 224) Alex: 5:00-6:30 (Bell 242)
Lecture 34 CSE 331 Nov 30, Graded HW 8 On Wednesday.
Lecture 39 CSE 331 Dec 9, Announcements Please fill in the online feedback form Sample final has been posted Graded HW 9 on Friday.
Lecture 27 CSE 331 Nov 6, Homework related stuff Solutions to HW 7 and HW 8 at the END of the lecture Turn in HW 7.
Lecture 38 CSE 331 Dec 2, Review Sessions etc. Atri: (at least ½ of) class next Friday Jiun-Jie: Extra office hour next Friday Jesse: Review Session.
Lecture 8 CSE 331. Main Steps in Algorithm Design Problem Statement Algorithm Problem Definition “Implementation” Analysis n! Correctness+Runtime Analysis.
Lecture 38 CSE 331 Dec 5, OHs today (only online 9:30-11)
Lecture 20 CSE 331 July 30, Longest path problem Given G, does there exist a simple path of length n-1 ?
Lecture 33 CSE 331 Nov 20, HW 8 due today Place Q1, Q2 and Q3 in separate piles I will not accept HWs after 1:15pm Submit your HWs to the side of.
Lecture 32 CSE 331 Nov 16, 2016.
Lecture 5 Dynamic Programming
Lecture 31 CSE 331 Nov 14, 2016.
Richard Anderson Lecture 29 NP-Completeness and course wrap-up
Lecture 26 CSE 331 Nov 2, 2016.
Lecture 23 CSE 331 Oct 26, 2016.
Lecture 16 CSE 331 Oct 5, 2016.
Lecture 17 CSE 331 Oct 3, 2014.
Lecture 5 Dynamic Programming
Lecture 31 CSE 331 Nov 13, 2017.
Lecture 34 CSE 331 Nov 26, 2012.
Lecture 21 CSE 331 Oct 21, 2016.
ICS 353: Design and Analysis of Algorithms
Lecture 36 CSE 331 Nov 29, 2017.
Lecture 36 CSE 331 Nov 30, 2016.
Lecture 35 CSE 331 Nov 27, 2017.
Lecture 34 CSE 331 Nov 20, 2017.
Lecture 17 CSE 331 Oct 7, 2016.
Lecture 33 CSE 331 Nov 18, 2016.
Lecture 33 CSE 331 Nov 17, 2017.
Lecture 35 CSE 331 Nov 28, 2016.
Lecture 24 CSE 331 Oct 25, 2013.
Lecture 26 CSE 331 Nov 1, 2017.
Lecture 22 CSE 331 Oct 23, 2017.
Lecture 23 CSE 331 Oct 25, 2017.
Lecture 24 CSE 331 Oct 29, 2012.
Lecture 23 CSE 331 Oct 24, 2011.
Lecture 16 CSE 331 Oct 4, 2017.
Lecture 37 CSE 331 Nov 30, 2011.
Dynamic Programming Longest Path in a DAG, Yin Tat Lee
Lecture 18 CSE 331 Oct 12, 2011.
Lecture 32 CSE 331 Nov 15, 2017.
Lecture 33 CSE 331 Nov 14, 2014.
Lecture 27 CSE 331 Oct 31, 2014.
Lecture 33 CSE 331 Nov 15, 2013.
Lecture 34 CSE 331 Nov 18, 2011.
Lecture 34 CSE 331 Nov 21, 2016.
Lecture 28 CSE 331 Nov 7, 2012.
Lecture 27 CSE 331 Nov 2, 2010.
Lecture 22 CSE 331 Oct 15, 2014.
Lecture 14 Shortest Path (cont’d) Minimum Spanning Tree
NP-Completeness Reference: Computers and Intractability: A Guide to the Theory of NP-Completeness by Garey and Johnson, W.H. Freeman and Company, 1979.
Lecture 39 CSE 331 Dec 5, 2011.
Lecture 24 CSE 331 Oct 24, 2014.
Lecture 36 CSE 331 Nov 28, 2011.
Lecture 36 CSE 331 Nov 30, 2012.
Lecture 37 CSE 331 Dec 2, 2016.
Lecture 23 CSE 331 Oct 24, 2011.
Lecture 26 CSE 331 Nov 1, 2010.
Lecture 32 CSE 331 Nov 12, 2014.
Richard Anderson Lecture 20 Shortest Paths and Network Flow
Lecture 13 Shortest Path (cont’d) Minimum Spanning Tree
Lecture 27 CSE 331 Nov 1, 2013.
Lecture 36 CSE 331 Nov 22, 2013.
Lecture 37 CSE 331 Dec 3, 2018.
Presentation transcript:

Lecture 37 CSE 331 Dec 1, 2017

Quiz 2 on Monday You can use two letter sized cheatsheets

Last HW up!

HW 9 solutions At the END of the lecture

Shortest Path Problem Input: (Directed) Graph G=(V,E) and for every edge e has a cost ce (can be <0) t in V Output: Shortest path from every s to t Assume that G has no negative cycle 1 100 -1000 899 s t Shortest path has cost negative infinity

When to use Dynamic Programming There are polynomially many sub-problems Richard Bellman Optimal solution can be computed from solutions to sub-problems There is an ordering among sub-problem that allows for iterative solution

Sub-problems OPT(u,i) = cost of shortest path from u to t with at most i edges

Today’s agenda Finish Bellman-Ford algorithm Analyze the run time

The recurrence OPT(u,i) = shortest path from u to t with at most i edges OPT(u,i) = min { OPT(u,i-1), min(u,w) in E { cu,w + OPT(w, i-1)} }

OPT(u,n-1) is shortest path cost between u and t Some consequences OPT(u,i) = shortest path from u to t with at most i edges OPT(u,i) = min { OPT(u, i-1), min(u,w) in E { cu,w + OPT(w,i-1)} } OPT(u,n-1) is shortest path cost between u and t Group talk time: How to compute the shortest path between s and t given all OPT(u,i) values

Longest path problem Given G, does there exist a simple path of length n-1 ?

Longest vs Shortest Paths

Two sides of the “same” coin Shortest Path problem Can be solved by a polynomial time algorithm Is there a longest path of length n-1? Given a path can verify in polynomial time if the answer is yes

Poly time algo for longest path?

Alternate NP definition: Guess witness and verify! P vs NP question P: problems that can be solved by poly time algorithms Is P=NP? NP: problems that have polynomial time verifiable witness to optimal solution Alternate NP definition: Guess witness and verify!

Pretty much all known proof techniques provably will not work Proving P ≠ NP Pick any one problem in NP and show it cannot be solved in poly time Pretty much all known proof techniques provably will not work

Proving P = NP Will make cryptography collapse Compute the encryption key! Prove that all problems in NP can be solved by polynomial time algorithms NP Solving any ONE problem in here in poly time will prove P=NP! NP-complete problems

A book on P vs. NP

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

If you are curious for more CSE 429 or 431: Algorithms CSE 396: Theory of Computation