CS514:
Advanced Topics in Network Science
Fall, 2023
Course
Objective
Networks
and graphs have become an indispensable ingredient in a variety of data mining
and machine learning problems with numerous applications. This course will
provide an in-depth understanding of network science, graph mining algorithms, and
their applications in a variety of real problems. It aims to provide a
comprehensive and in-depth introduction of the fundamental principles and
techniques of network science.
·
Be able to understand the key concepts and underlying
principles of network analysis techniques, including graph proximity, matrix
and tensor, graph neural networks, graph connectivity, network of networks.
·
Be able to apply the key network science
techniques to realistic setting, evaluate and analyze the analysis results.
Basic
Information
Class
meeting: 4025 CIF, 9:30am – 10:45am
W/F
Instructor: Hanghang Tong (htong@illinois.edu)
TA:
·
Zhe Xu (zhexu3@illinois.edu)
Office Hours: [All CT time, all on Zooms. Note that each of us has a
different zoom link & pwd. Please refer to
announcement from canvas/piazza]
· Hanghang Tong: 8:30-9:10am CT, Friday
· Zhe Xu: 11:00-11:30am CT, Monday & Tuesday
Online resources:
·
Piazza: https://piazza.com/illinois/fall2023/cs514
·
Canvas
Schedule
(Tentative, subject to slight adjustment)
·
Lecture 1: Logistics & Introduction (week
1)
·
Lecture 2: Graph Proximity (weeks 1 & 2)
·
Lecture 3: Matrix & Tensors (weeks 3 &
4 )
·
Lecture 4: Graph Neural Networks (weeks 4
& 5 )
·
Lecture 5: Graph Anomaly Detection (weeks 6
& 7 )
·
Lecture 6: Graph Connectivity Optimization
(weeks 7 & 8 )
·
Lecture 7: Network Alignment (weeks 9 & 10 )
·
Lecture 8: Fair Network Mining (weeks 10 &
11 )
·
Lecture 9: Knowledge Graphs (weeks 12 & 13 )
·
Lecture 10: Network of Networks, Network of X
(week 14 )
·
Lecture 11: Network of Team Science (week 15 )
·
Lecture 12: Optimal Deep Graph Learning (week
16)
Coursework,
Grading and Key Dates
·
Two
assignments: 20% in total (equal weights)
o First
assignment: 8/25/2023 out; 10/4/2023 due
o Second
assignment: 10/13/2023 out; 11/17/2023 due
·
Class
project: 30%
o Proposal
(2%): due on 9/13/2023
o Mid-term
report (8%): due on 10/20/2023
o Final
report (20%): due on 12/10/2023
o Individual
project or group project (3 members at most per group)
·
Midterm
exam: 20% in total
o Date:
9:30-10:45am CT, 10/11/2023
o Location:
4025 CIF
·
Final exam:
30% in total
o Date: TBD
o Location:
TBD
Textbooks
No
required textbook for this course. We will mainly use research papers and
slides for lectures.
Reference:
·
Jiawei Han, Jian Pei and Hanghang
Tong, Data Mining: Concepts and Techniques (4th ed), Morgan &
Claypool, 2022
·
Charu C. Aggarwal, Data Mining: The Textbook, Springer, 2015
·
P.-N. Tan, M. Steinbach and V. Kumar,
Introduction to Data Mining, Wiley, 2005 (2nd ed. 2016)
·
Mohammed J. Zaki and Wagner
Meira Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms,
Cambridge University Press, 2014
Mental Health
Diminished mental health,
including significant stress, mood changes, excessive worry, substance/alcohol
abuse, or problems with eating and/or sleeping can interfere with optimal
academic performance, social development, and emotional wellbeing. The
University of Illinois offers a variety of confidential services including
individual and group counseling, crisis intervention, psychiatric services, and
specialized screenings at no additional cost. If you or someone you know
experiences any of the above mental health concerns, it is strongly encouraged
to contact or visit any of the University’s resources provided below. Getting
help is a smart and courageous thing to do -- for yourself and for those who
care about you.
Counseling Center: 217-333-3704,
610 East John Street Champaign, IL 61820
McKinley Health
Center:217-333-2700, 1109 South Lincoln Avenue, Urbana, Illinois 61801
Sexual Misconduct Reporting Obligation
The
University of Illinois is committed to combating sexual misconduct. Faculty and
staff members are required to report any instances of sexual misconduct to the
University’s Title IX Office. In turn, an individual with the Title IX Office
will provide information about rights and options, including accommodations,
support services, the campus disciplinary process, and law enforcement options.
A
list of the designated University employees who, as counselors, confidential
advisors, and medical professionals, do not have this reporting responsibility
and can maintain confidentiality, can be found here: wecare.illinois.edu/resources/students/#confidential.
Other
information about resources and reporting is available here: wecare.illinois.edu.
Academic Integrity
The
University of Illinois at Urbana-Champaign Student Code should also be
considered as a part of this syllabus. Students should pay particular attention
to Article 1, Part 4: Academic Integrity. Read the Code at the following URL: http://studentcode.illinois.edu/.
Academic
dishonesty may result in a failing grade. Every student is expected to review
and abide by the Academic Integrity Policy: https://studentcode.illinois.edu/article1/part4/1-401/. Ignorance is not an excuse for any academic
dishonesty. It is your responsibility to read this policy to avoid any
misunderstanding. Do not hesitate to ask the instructor(s) if you are ever in
doubt about what constitutes plagiarism, cheating, or any other breach of
academic integrity.
Religious Observances
Illinois
law requires the University to reasonably accommodate its students' religious
beliefs, observances, and practices in regard to
admissions, class attendance, and the scheduling of examinations and work
requirements. You should examine this syllabus at the beginning of the semester
for potential conflicts between course deadlines and any of your religious
observances. If a conflict exists, you should notify your instructor of the
conflict and follow the procedure at https://odos.illinois.edu/community-of-care/resources/students/religious-observances/ to request appropriate accommodations. This
should be done in the first two weeks of classes.
Disability-Related Accommodations
To obtain disability-related
academic adjustments and/or auxiliary aids, students with disabilities must contact
the course instructor and the Disability Resources and Educational Services
(DRES) as soon as possible. To contact DRES, you may visit 1207 S. Oak St.,
Champaign, call 333-4603, e-mail disability@illinois.edu or go to https://www.disability.illinois.edu. If you are concerned you have a
disability-related condition that is impacting your academic progress, there
are academic screening appointments available that can help diagnosis a
previously undiagnosed disability. You may access these by visiting the DRES
website and selecting “Request an Academic Screening” at the bottom of the page.
Family Educational Rights and Privacy Act
(FERPA)
Any
student who has suppressed their directory information pursuant to Family
Educational Rights and Privacy Act (FERPA) should self-identify to the
instructor to ensure protection of the privacy of their attendance in this
course. See https://registrar.illinois.edu/academic-records/ferpa/ for more information on FERPA.
Assuring Non-Hostile Work Environment
In order to assure a non-hostile work environment for
course staff, we will strictly enforce the following policy for the future
assessment, including exams, assignments and course project. Any assessment
containing language that conventionally would be judged as obscene, threatening
violence, or of a clearly derogatory nature will be given a 0 without further
grading.
Statement on CS CARES and CS
Values and Code of Conduct
All members of the Illinois
Computer Science department - faculty, staff, and students - are expected to
adhere to the CS Values and Code of Conduct. The CS CARES Committee is available to serve as a resource to
help people who are concerned about or experience a potential violation of the
Code. If you experience such issues, please contact the CS CARES Committee. The instructors of this course are also
available for issues related to this class.