ECSA122A Instructor Page, Winter 2018

ECS122A
Algorithm Design and Analysis
Winter 2018

Instructor:

Zhaojun Bai,
Office: 3005 Kemper Hall
Phone: 752-4874
Email: bai at cs.ucdavis.edu

Teaching Assistants:

Nima Joharizadeh (johari at ucdavis.edu)

Kenan Nalbant (kanalbant at ucdavis.edu)

Yuan Pan (yapan at ucdavis.edu)

Lectures:

M.W.F. 12:10pm - 1:00pm
Hunt 100

Discussions:

TA	Section	Time	Place
Yuan	A01 (CRN51558)	Mon. 10-10:50	Olson 106
Nima	A02 (CRN51559)	Wed. 10-10:50	Olson 106
Kenan	A03 (CRN51560)	Wed. 3:10-4:00	Chemistry 176

Website for discussion sessions

Office Hours:

Day	Time	Place
Mondays	3:00 - 4:00	Kemper 3005, Bai
	5:00 - 7:00	Kemper 53, Nima
Tuesdays	10:00 - 11:00	Kemper 55, Yuan
	5:00 - 7:00	Kemper 53, Kenan
Wednesdays	2:00 - 3:00	Kemper 3005, Bai
	5:00 - 6:00	Kemper 53, Kenan
Thursdays	6:00-8:00	Kemper 53, Yuan
Fridays	10:00 -- 11:00	Kemper 3005, Bai
	5:00 -- 6:00	Kemper 53, Nima

Course Objectives:

The notion of an algorithm is fundamental to all of computer science. In this course, we study methods for designing efficient algorithms, evaluating their performance, and ways of establishing precise limits on the possible effectiveness of classes of algorithms.

Textbook and lecture notes:

Textbook: Introduction to Algorithms (3rd edition) by T. Cormen, C. Leiserson, R. Rivest and C. Stein, MIT Press, 2009
A collection of lecture notes is available at Davis Copy Max, 232 3rd Street, phone: 758-2311.
Updated lecture notes and additional handouts will be posted on this site throughout the quarter.

Prerequisites

ECS20 and ECS60.

Course Outline

Introduction and foundations (Ch.1-3)
Algorithm design paradigms:
- Divide-and-conquer (Ch.4)
- Dynamic programming (Ch.15)
- Greedy algorithms (Ch.16)
Algorithms on graphs and trees (Ch.22-25)
NP-completeness and approximate algorithms (Ch.34-35)

Homeworks:

There will be about eight problem sets. The material in this class can only be learned by doing lots of problems, so the homework is very important. If you do not do substantially all of the problem sets, then do not expect to pass.
Your homework should be your own work. It is a matter of intellectual honesty to write your homework strictly by yourself. Using solutions from any other source is not allowed.
~~Homeworks are to be turned in at the beginning of lecture on the due date, or be deposited in ECS122A Homework Box in Room 2131, Kemper Hall by 4:00pm on the due date.~~
No late homework will be accepted! ~~No email homework!~~ see the annoucement at the top of this page

Exams (All exams are closed-book, no notes allowed):

Midterms: February 5 and March 5
Final: March 20, 6:00-8:00pm

Grading:

Homeworks: 20%
Midterm exams: 40%
Final exam: 40%

Grading may reflect the clarity of your presentation as well as the correctness of your answers.

Regrading of homeworks and midterm exams is only considered within 5 days from the return day. Regrading request must be submitted in writing.

Online Info:

Annoucements, handouts and homework assignments will be posted at the following sites. They get updated frequently throughout the quarter.

canvas
The class webpage http://www.cs.ucdavis.edu/~bai/ECS122A

Lecture-by-Lecture summaries, handouts and homework assignments

Date Topics Handouts/Homeworks

1/8 I. Introduction and getting started LN: Introduction and getting started
Reading: Chaps. 1 and 2
Review: linear recurrences (ECS20)
Warmup exercise

1/10 I. Introduction and getting started (2/3) Problem set 1

1/12 I. Introduction and getting started
II. Asymptotic notations
LN: Asymptotic notations
Reading: Section 3.1

1/15 holiday, no class

1/17 II. Asymptotic notations
III. Divide-and-Conquer (DC) recurrences
LN: DC recurrences
Reading: Section 3.2
Problem set 2

1/19 III. Divide-and-Conquer recurrences
Reading: Section 4.4

1/22 IV. DC algorithms: maximum-subarray
IV. DC algorithms: Strassen's method
LN: maximum-subarray
LN: Strassen
Reading: Sections 4.1 and 4.2

1/24 IV. DC algorithms: the closest pair
LN: closest pair
Problem set 3

1/26 V. Greedy algorithms: activity selection
LN: activity selection
Reading: 16.1

1/29 V. Greedy algorithms: Huffman codes
LN: Huffman codes
Reading: sections 16.2 and 16.3

1/31 V. Greedy algorithms: knapsack problem
LN: knapsack
Problem set 3 due
Extra reading: money changing

2/2 VI. Dynamic programming: rod cutting
Brief review for midterm I LN: rod cutting
Reading: section 15.1
Problem set 4

2/5 Midterm 1 Review checklist, Slides

2/7 VI. Dynamic programming: matrix-chain product LN: matrix-chain product
Reading: sections 15.2 and 15.3

2/9 VI. Dynamic programming: longest common subsequence LN: LCS
Reading: section 15.4

2/12 VI. Dynamic programming: LCS and edit distance LN: edit distance
Problem set 5

2/14 VI. Dynamic programming: Knapsack problem and summary LN: knapsack revisited
Handout on knapsack
Reading: section 15.3

2/16 VII. Graph algorithms: Intro and BFS
LN: Graph intro
LN: BFS
Reading: Sections 22.1 and 22.2, Appendix B.4

2/19 holiday, no class ...

2/21 VII. Graph algorithms: DFS
LN: DFS
Handout: DFS
Reading: sections 22.3 and 22.4
Problem set 6

2/23 VII. Graph algorithms: DFS apps and MST
LN: DFS apps
Reading: section 22.4

2/26 VII. Graph algorithms: MST
LN: MST
Reading: Chap. 23

2/28 VII. Graph algorithms: Shortest-path I - intro
LN: Shortest-path intro
Reading: Chap. 24 (pp.643-650)

3/2 VII. Graph algorithms: Shortest-path II - Bellman-Ford
Brief review for midterm II LN: Shortest-path algs.
Reading: section 24.1
Problem set #7

3/5 Midterm 2 Review checklist, Slides

3/7 VII. Graph algorithms: Shortest-path III - Dijkstra and DAG LN: Shortest-path algs.
Reading: sections 24.2 and 24.3

3/9 VII. Graph algorithms: Shortest-path III - Dijkstra and DAG Extra LN: Shortest-path profs.

3/12 VIII. NP-completeness I LN: NPC-intro
Handout: NPC

3/14 VIII. NP-completeness II LN: NPC-p vs np
Questions on NPC (ans@canvas)

3/16 VIII. NP-completeness III
Final review Extra LN on NPC
Final review checklist, slides

3/19
Monday extra office hours:
3:00 - 5:00pm, Kenan, 55 Kemper
5:00 - 7:00pm, Nima, 55 Kemper

3/20
Tuesday extra office hours:
10:00 - 12:00noon, Yuan, 55 Kemper
2:00 - 4:00pm, Bai, 3005 Kemper
Final Exam:
6:00-8:00pm, 100 Hunt ...

Date	Topics	Handouts/Homeworks
1/8	I. Introduction and getting started	LN: Introduction and getting started Reading: Chaps. 1 and 2 Review: linear recurrences (ECS20) Warmup exercise
1/10	I. Introduction and getting started (2/3)	Problem set 1
1/12	I. Introduction and getting started II. Asymptotic notations	LN: Asymptotic notations Reading: Section 3.1
1/15	holiday, no class
1/17	II. Asymptotic notations III. Divide-and-Conquer (DC) recurrences	LN: DC recurrences Reading: Section 3.2 Problem set 2
1/19	III. Divide-and-Conquer recurrences	Reading: Section 4.4
1/22	IV. DC algorithms: maximum-subarray IV. DC algorithms: Strassen's method	LN: maximum-subarray LN: Strassen Reading: Sections 4.1 and 4.2
1/24	IV. DC algorithms: the closest pair	LN: closest pair Problem set 3
1/26	V. Greedy algorithms: activity selection	LN: activity selection Reading: 16.1
1/29	V. Greedy algorithms: Huffman codes	LN: Huffman codes Reading: sections 16.2 and 16.3
1/31	V. Greedy algorithms: knapsack problem	LN: knapsack Problem set 3 due Extra reading: money changing
2/2	VI. Dynamic programming: rod cutting Brief review for midterm I	LN: rod cutting Reading: section 15.1 Problem set 4
2/5	Midterm 1	Review checklist, Slides
2/7	VI. Dynamic programming: matrix-chain product	LN: matrix-chain product Reading: sections 15.2 and 15.3
2/9	VI. Dynamic programming: longest common subsequence	LN: LCS Reading: section 15.4
2/12	VI. Dynamic programming: LCS and edit distance	LN: edit distance Problem set 5
2/14	VI. Dynamic programming: Knapsack problem and summary	LN: knapsack revisited Handout on knapsack Reading: section 15.3
2/16	VII. Graph algorithms: Intro and BFS	LN: Graph intro LN: BFS Reading: Sections 22.1 and 22.2, Appendix B.4
2/19	holiday, no class	...
2/21	VII. Graph algorithms: DFS	LN: DFS Handout: DFS Reading: sections 22.3 and 22.4 Problem set 6
2/23	VII. Graph algorithms: DFS apps and MST	LN: DFS apps Reading: section 22.4
2/26	VII. Graph algorithms: MST	LN: MST Reading: Chap. 23
2/28	VII. Graph algorithms: Shortest-path I - intro	LN: Shortest-path intro Reading: Chap. 24 (pp.643-650)
3/2	VII. Graph algorithms: Shortest-path II - Bellman-Ford Brief review for midterm II	LN: Shortest-path algs. Reading: section 24.1 Problem set #7
3/5	Midterm 2	Review checklist, Slides
3/7	VII. Graph algorithms: Shortest-path III - Dijkstra and DAG	LN: Shortest-path algs. Reading: sections 24.2 and 24.3
3/9	VII. Graph algorithms: Shortest-path III - Dijkstra and DAG	Extra LN: Shortest-path profs.
3/12	VIII. NP-completeness I	LN: NPC-intro Handout: NPC
3/14	VIII. NP-completeness II	LN: NPC-p vs np Questions on NPC (ans@canvas)
3/16	VIII. NP-completeness III Final review	Extra LN on NPC Final review checklist, slides
3/19 Monday	extra office hours: 3:00 - 5:00pm, Kenan, 55 Kemper 5:00 - 7:00pm, Nima, 55 Kemper
3/20 Tuesday	extra office hours: 10:00 - 12:00noon, Yuan, 55 Kemper 2:00 - 4:00pm, Bai, 3005 Kemper Final Exam: 6:00-8:00pm, 100 Hunt	...

Important announcement:

Office hour from 5-6 on March 2 will be at Prof. Bai's office, 3005 Kemper Hall
2/20, There is a ``Meet the Faculty'' meeting this Friday, February 22 from noon to 2pm in Kemper 1121. CS professors would love to chat with you about our exciting classes, the different majors hosted in the department, opportunities on and off campus related to Computer Science, and the future of Computer Science at UC Davis. This event is open to ALL interested undergraduates. Whether you're a CS student, or a student interested in joining CS.
1/30, Here is a link the website of discussion sessions
1/26, All homework will be handled electronically through Gradescope rather than the homework box, starting from Homework #2 due 4:00pm, Jan. 24. You can be added to the course's gradescope through your UCD email address to sign in. The access code to the course is 92RJDJ. For submissions, make sure your documents are PDFs. If you're scanning a handwritten document for submission we recommend that you write your solutions on white paper with pen for maximum legibility (if we can't read your paper then we won't be able to grade it). This link contains further instructions on the workflow. If you have any questions feel free to email to Kenan: kanalbant@ucdavis.edu

Maintained by Zhaojun Bai

ECS122A Algorithm Design and Analysis Winter 2018

ECS122A
Algorithm Design and Analysis
Winter 2018