CPS237

 

Spring 2002

 

RANDOMIZED ALGORITHMS


Current Homework:

HM1 due Jan 23: M&R: problems 1.1,1.2,1.3,1.4,1.5,1.8,1.10

 

Class Schedule and Class Notes:

 

Date

Topic

Readings

 

Wed Jan 9

No Class (Makeup extra lecture Jan 16)

 

 

Fri  Jan 11

Introduction to Randomized Algorithms:

Notes(DK): Introduction to Randomized Algorithms: Examples of Quicksort, BSP, MINCUT  PS, PDF

Ch. 1, pp 3-27

Appendix B: pp 433-437

 

Mon Jan 14

More Examples of Randomized Algorithms:

Notes(JR):: Probability Theory Review

Notes(AB):Why Ranomized Algs and  Example: partitioning a 3-colorable graph.

Notes(AB): Examples: Secretly computing an average, k-wise independence, linearity of expectation, quicksort.

Ch. 1, pp 3-27

Appendix B: pp 433-437

 

Wed Jan 16 (extra lecture)

Randomized Game-Theoretic Techniques:

Notes(DK): Complexity theory, game tree evaluation. PS, PDF (Chapt. 2.1,2.2)

Notes(DK): Adelman's Theorem, game theory, lower bounds. PS, PDF (Chapt. 2.3)

Ch. 2: pages 28-42

 

Fri  Jan 18

Probabilistic Analysis: Moments and Deviations:

Notes(DK): Coupon collecting, stable marriage, Markov inequality. PS, PDF (Chapt. 3.2,3.5,3.6)

Notes(AB):Balls'n'boxes, lower bounds, Spencer's graduation game. (Chapt 2.2.2, 3.1, 3.6, 5.1)

Ch. 3: pages 43-66

Appendix C: Basic Probability Theory, pages 438-446

 

Mon  Jan 21

No Class (Martin Luther Holiday)

 

 

Wed  Jan 23

Probabilistic Analysis: Tail Inequalities:

Notes(DK): Chebyshev, Two point sampling, Chernoff. PS, PDF

Notes(AS): Facts related to the Chernoff-Hoeffding bounds PS PDF

Notes(AB): probabilistic inequalities, Chernoff bounds, complexity classes. PS, PDF. (Chap. 2.3, 3.1-3.4, 4.1)

Ch. 3: pages 43-66

Ch. 4: pages 67-100

 

Fri  Jan 25

The Probabilistic Method:

Notes(AB):Randomized rounding, probabilistic method. (Chap 4.3, 5.1, 5.2, 5.6)

Notes(AS): Basics regarding expectations and the probabilistic method PS PDF

Notes(AS): The vertex-connectivity of random graphs PS PDF

Ch. 5: pages 101-126

 

Mon Jan 28

 

The Probabilistic Method:

Notes(DK): Median finding, Routing. PS, PDF (Chapt 4.2,5.4)

Notes(AS): The Lov'asz Local Lemma and Packet Routing PS PDF (Chapt 4.4,5.4.5)

Ch. 5: pages 101-126

 

Wed Jan 30

The Probabilistic Method:

Notes(DK): Method of conditional Probabilities and Expectations, Fingerprinting. PS, PDF

Notes(AS): Pessimistic estimators PS PDF

Advanced Reading: Notes(AB):Analysis of local optimization algorithms. Also [Aldous-Vazirani, FOCS '94, pages 492-501] and [Dimitriou-Impagliazzo, STOC '96, pages 304-313]

Ch. 5: pages 101-126

 

Wed Feb 6

The Probabilistic Method:

Notes(DK): Expanders, Wiring, MAX SAT. PS, PDF (Chapt 5.3,5.4)

 

Ch. 5: pages 101-126

 

 

Fri  Feb 8

Randomized Algebraic Methods

Notes(JR): Hashing Polynomials and Algebraic Equations PS, PDF

Notes(DK): Fingerprints by Polynomials, Perfect Matching, Hashing.  PS, PDF.

Notes(AB): NP in PCP(poly,1). PS, PDF. (Chap 7.1, 7.7, 7.8)

Ch. 7: pages 161-196

 

 

Wed Feb 13

Randomized Data Structures:

Notes(JR): Universal Hash Functions PS, PDF

Notes(DK): More Hashing, Perfect Hash Families, Treaps.  PS, PDF

Notes(AB):Universal and perfect hashing. (Chap. 8.4, 8.5)

Ch. 8: pages 197-233

 

 

Fri  Feb 15

Randomized Data Structures:

Notes(DK): Treaps, Skip Lists, Shortest Paths. PS, PDF

 

Ch. 8: pages 197-233

 

Mon Feb 18

Randomized Data Structures:

Notes(DK): Shortest Paths. PS, PDF

Ch. 8: pages 197-233

 

Fri  Feb 22

Geometric Algorithms:

Notes(DK): Point location, Randomized incremental construction. PS, PDF

Ch. 9: pages 234-277

 

Mon  Feb 25

Randomized Geometric Algorithms:

Notes(DK): Randomized incremental construction, Trapezoidal decomposition. PS, PDF

Ch. 9: pages 234-277

 

Wed Feb 27

(extra lecture)

Randomized Geometric Algorithms and Linear Programming:

Notes(DK): Trapezoidal decomposition/search structure, Linear Programming. PS, PDF

Ch. 9: pages 234-277

 

Fri  March 1

Randomized Geometric Algorithms and Linear Programming:

Notes(DK): Linear Programming. PS, PDF

Ch.9: pages 234-277

 

Mon March 4

Randomized Graph Algorithms:

Notes(DK): Minimum cuts, minimum spanning trees. PS, PDF

Notes(LS): Min-Cut  PS PDF

Notes(DK): Minimum spanning trees.  PS, PDF

Notes(AB)::A monte-carlo Minimum Cut algorithm. (Chap. 1.1, 10.2)

Notes(DK): Polling, Minimum Cut, Transitive Closure. PS, PDF

Ch. 10: pages 278-305

 

Wed March 6

Markov Chains and Random Walks:

Notes(DK): Markov Chains, Random Walks. PS, PDF

Notes(AB):Random walks and cover times. (Chap 6.1, 6.3, 6.4, 6.5)

Ch. 6: pages 127-160

 

week March 11

No Class (Spring Break Week)

 

 

Wed March 20

3:45-5pm

Markov Chains and Random Walks:

Notes(DK): Sampling using Markov Chains, Eigenvalues. PS, PDF

Notes(DK): Markov Chains for Sampling, Volume, Expander Walks, Coupling. PS, PDF

Ch. 6: pages 127-160

 

 

 

Fri  March 22

Markov Chains and Random Walks:

Notes(AB):Resistive networks, existence of expanders. (Chap 5.3, 6.2)

Notes(AB):Expanders, eigenvalues, and rapid mixing. Randomized Clique hardness reduction. PS, PDF.

Notes(AB):Amplifying randomness via random walks on expanders. (Chap 6.7, 6.8)

Notes(LS): Expander graphs and pseudorandom number generators for BPP  PS PDF

Ch. 6: pages 127-160

 

Mon March 25

Markov Chains and Random Walks:

Notes(AB):intro to approx counting| Noga's quick proof. PS, PDF. (Chap 11.1)

Notes(LS): #SAT PS PDF

Notes(DK): DNF Counting. PS, PDF

Notes(LS): Approximate #DNF(cont.) and the Chernoff Bound PS PDF

Ch. 11: pages 306-334

 

Wed March 27

Randomized Approximate Counting:

Notes(AB):Approximating the Permanent, part 1. Chap 11.3)

Notes(AB):Approximation the Permanent, part 2.

Ch. 11: pages 306-334

 

 

Mon  April 1

 

No Class (on travel; give extra lecture Feb 27)

 

 

 

Fri  April 5

No Class (on travel; give extra lecture April 17)

 

 

Weds April 10

Randomized Parallel and Distributed Algorithms:

Notes(DK):  Coupling, Parallel Algorithms, Sorting. PS, PDF

Ch. 12: pages 335-367

 

Fri  April 12

Parallel and Distributed Algorithms:

Notes(DK): Maximal Independent Set, Perfect Matching. PS, PDF

Notes(LS): Finding a maximal independent set is in NC  PS PDF

Ch. 12: pages 335-367

 

Mon  April 15

Randomized Online Algorithms:

Notes(AB):Randomized algorithms for on-line problems. (Chap 13.1, 13.3)

Reading: Motwani & Raghavan Chapter 13: pages 368-391

Ch. 13: pages 368-391

 

Weds  April 17(extra lecture)

Randomized Number Theory and Algebra:

Notes(AB):Intro to number-theoretic algorithms. (Chap 14)

Ch. 14: pages 392-428

 

Fri  April 19

 

Notes(AB):Randomized algorithms for primality testing.

Ch. 14: pages 392-428

 

 

Note: Class lecture notes indicated by DK, AB, AS, LS were prepared by the following (and used with their prior permissions):

 

Notes(JR): due to John Reif 

Notes(DK): due to David Karger & students, MIT

Notes(AB): due to Avrim Blum, CMU

Notes(AS): due to Aravind Srinivasan, Univ. Maryland

Notes(LS): due to Leonard Schulman, Georgia Institute of Technology

 


John Reif