COMPSCI 311: Introduction to Algorithms (Section 2)

Spring 2019

Marius Minea

Welcome to the Spring 2019 homepage for COMPSCI 311: Introduction to Algorithms (Section 2).
This course has similar lectures with Section 1 (taught by Dan Sheldon). The sections share TAs and graders, Moodle, Piazza and Gradescope sites, and there will be common assignments, quizzes, and midterms, but finals are on different days.

Basic Information

Instructor: Marius Minea (marius at cs), office: LGRC A261, office hours Tue 5-6 pm, Thu 1:15-2 pm, Fri 3:30-4:30 pm
Lectures: Mon,Wed 4:00 - 5:15pm, Integrative Learning Center S140
Textbook (required): Algorithm Design by Jon Kleinberg and Éva Tardos.
Moodle
Piazza
TAs: Jesse Lingeman (lingeman at cs), Karine Tung (karine@cs), Raghavendra Addanki (raddanki at cs), Subhojyoti Mukherjee (subho at cs)

Description This course will introduce you to algorithms in a variety of areas of interest, such as sorting, searching, string-processing, and graph algorithms. You will learn to study the performance of various algorithms within a formal, mathematical framework. You will also learn how to design very efficient algorithms for many kinds of problems. Mathematical experience (as provided by COMPSCI 250) is required. You should also be able to program in Java, C, or some other closely related language. Prerequisites: COMPSCI 187 and either COMPSCI 250 or MATH 455.

Exams

Midterm 1: Thursday, February 21 from 7-9pm ILC N151
Midterm 2: Thursday, April 11 from 7-9pm in ILC N151
Final exam: Monday, May 6, 3:30-5:30 pm, Thompson Hall 106

Homework (dates are tentative)

HW 1: released 1/24, due ~~Thu 2/7~~ Fri 2/8 at 11:59pm
HW 2: released 2/7, due Mon 2/18 at 11:59pm
HW 3: released 2/22, due Fri 3/8 at 11:59pm
HW 4: released 3/13, due Fri 3/29 at 11:59pm
HW 5 released 3/29, due Mon 4/8 at 11:59pm
HW 6: released 4/12, due Fri 4/26 at 11:59pm

Schedule
The schedule is tentative and will be updated as class progresses.

Week		Date	Topics	Readings
1	Lec 1	1/23	Introduction and Stable Matching	Chapter 1.1
	Dis 1	1/25
2	Lec 2	1/28	Algorithm Analysis and Asymptotics	Ch 2.1, 2.2
	Lec 3	1/30	Algorithm Analysis, Graphs	Ch 3.1, 3.2
	Dis 2	2/1
3	Lec 4	2/4	Graphs	Ch 3.3, 3.4
	Lec 5	2/6	Graphs	Ch 3.5, 3.6
	Dis 3	2/8
4	Lec 6	2/11	Greedy	Ch 4.1
	Lec 7	2/13	Greedy	Ch 4.2
	Dis 4	2/15
5		2/18	NO CLASS - PRESIDENT'S DAY
	Lec 8	2/19	Greedy (Monday Schedule)	Ch. 4.4
	Lec 9	2/20	Greedy	Ch. 4.5, 4.6
	Dis 5	2/22
6	Lec 10	2/25	Divide and Conquer	Ch. 5.1, 5.2
	Lec 11	2/27	Divide and Conquer	Ch. 5.4, 5.5
	Dis 6	1/1
7	Lec 12	3/4	Divide and Conquer	Ch. 5.2
	Lec 13	3/6	Dynamic Programming	Ch. 6.1, 6.2
	Dis 7	3/8
			SPRING BREAK (3/10-3/17)
8	Lec 14	3/18	Dynamic Programming	Ch. 6.3, 6.4
	Lec 15	3/20	Dynamic Programming	Ch. 6.6
	Dis 8	3/22
9	Lec 16	3/25	Dynamic Programming IV	Ch. 6.8
	Lec 17	3/27	Network Flow	Ch. 7.1, 7.2
	Dis 9	3/29
10	Lec 18	4/1	Network Flow	Ch. 7.2, 7.3
	Lec 19	4/3	Network Flow III	Ch. 7.5
	Dis 10	4/5
11	Lec 20	4/8	Intractability	Ch. 8.1
	Lec 21	4/10	Intractability	Ch. 8.2, 8.3
	Dis 11	4/12
12		4/15	NO CLASS - PATRIOTS' DAY
	Lec 22	4/17	Intractability (Monday Schedule)	Ch 8.3
	Dis 12	4/17
13	Lec 23	4/22	Intractability	Ch 8.4
	Lec 24	4/24	Approximation Algorithms	Ch 11.1, 11.2
	Dis 13	4/26
14	Lec 25	4/29	Randomized Algorithms	Ch 13.1, 13.2, 13.4
	Lec 26	5/1	Review

Grading

Participation (10%): Discussion section activities (7.5%) and in-class quizzes (iClicker) (2.5%). The lowest two discussion sections and three clicker scores will be dropped.
Homework (25%) + Weekly Moodle quiz (5%)
Midterm 1 (20%): Focus on first third of the class.
Midterm 2 (20%): Focus on second third of the class.
Final (20%): Covers all lectures.

Resources

Required Textbook: Algorithm Design by Jon Kleinberg and Éva Tardos.
Optional: Companion slides for Kleinberg and Tardos
Optional: Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein
Optional: Algorithms by Dasgupta, Papadimitriou, and Vazirani

Collaboration and Academic Honesty

Homework: Collaboration is encouraged on homework assignments. However, you should first understand and attempt the problem individually. Each student must write their own solutions. Looking at solutions from other students or any other source (including the web) is a violation of the Academic Honesty Policy. Formal charges will be pursued if cheating is suspected.
Quizzes: No collaboration is allowed, but you may use the book and lecture notes. Formal chages will be pursued if cheating is suspected.
Discussion: Exercises during discussion sections will be completed in assigned groups.
Exams: Closed book and no electronics. Cheating will result in an F in the course.

Online Quizzes

Quizzes will be issued before the weekend and must be submitted before 8pm on Monday. No credit will be given for late quizzes, but the lowest scoring quiz will be dropped.

Homework Submission and Late Policy

Homework will be submitted via GradeScope. You may type up your answers in Latex and compile to pdf (preferred) or hand-write your homework and scan to pdf. If scanned, the pdf must be rotated correctly, scanned at high quality, and readable at a standard letter size. If the homework is not submitted in the correct format, it will not receive credit. Unreadable work, scratching out, etc. will not be graded. You should view the pdf once you submit to ensure it meets these minimum standards. Review the gradescope submission workflow (here and here) to make sure you upload and annotate your homework correctly.

Late policy

A 50% penalty will be applied for homework that is late by up to 24 hours. Homework that is late by more than 24 hours receives no credit. However, each student is allowed to submit one homework up to 24 hours late without penalty.

Discussion Section

The discussion section will be used every week except when noted on the course schedule and will consist of exercises to practice solving problems in small groups. Attendance is required and counts towards the course grade.

Inclusivity

Please read the CICS inclusivity statement, copied here:

The College of Computer and Information Sciences shares UMass Amherst’s commitment to diversity. We welcome all individuals regardless of age, background, citizenship, disability, sex, education, ethnicity, family status, gender, gender identity, geographical origin, language, military experience, political views, race, religion, sexual orientation, socioeconomic status, and work experience. We expect all members of our community to treat others with respect and civility.

Accomodations for Disabilities

If you have a disability and would like to request accommodations, please contact Disability Services, located in 161 Whitmore Hall, (413) 545-0892. If you are eligible, they will grant you accommodations and notify the instructors.