Fall 2000 CS Course Listings

Following are the PG courses that we are offering in the Fall 2000/2001:

Archive of past courses

Course code: COMP660E

Course title: Topics in Computer and Communication Networks: Multimedia networking

Instructor: Dr. Gary Chan

Room:

Telephone: x6990

Email:

WWW page: http://cse.hkust.edu.hk/~gchan

Area in which course can be counted: CE

Course Description:

Advanced topics in communicaiton networks, including issues in high speed networking (ATM and switch design), multimedia communication (voice over IP, video networking, video encoding standards, etc.), and protocol design (multimedia standards, multicast protocols, QoS, etc.), and network analysis.

Course Objectives:

To familiarize graduate students with the current advanced networking terminologies and technologies.

Course Outline/Contents:

  • Review of TCP/IP
  • Network simulation
  • Multimedia systems and multicast protocols
  • Video processing and networks
  • QoS and RSVP
  • ATM and switch design
  • Network protocol design and analysis
  • Network control and economics
  • Mobile IP and wireless networking
  • Switching in IP networks
  • Optical networking

Text Book:

Assorted textbooks and reference materials

Reference Books/materials:

Grading Scheme:

  • 1 programming assignment (10%)
  • 2 midterms (50%)
  • Final presentation (10%)
  • A survey paper (30%)

Pre-requisites/Background needed:

Networking background equivalent to COMP 361 and COMP 362

Available for final year UG students to enroll: Ok

Minimum CGA required for UG students: A- or above

Course code: COMP660F

Course title: Topics in Computer and Communication Networks: Quality of Service

Instructor: Dr. Brahim Bensaou

Room:

Telephone:

Email: (to be confirmed)

WWW page: http://cse.hkust.edu.hk/~csbb/ (to be confirmed)

Area in which course can be counted: CE

Course Description:

Advanced topics in communication networks, focused on Internet and techniques involved in providing quality of service. The course is structured in three parts. The first part introduces Internet architecture, protocols and the different functionalities they provide. The second part focuses on quality of service in Internet as it is known today as well as newly introduced architectures for supporting QoS in future Internet. This part is mostly based on recent research results and publications as well as IETF drafts. The third part explores some issues on QoS in wireless Internet.

Course Objectives:

To familiarize graduate students with the current advances in quality of service provisioning in Internet.

Course Outline/Contents:

  • Review of Internet Architecture and protocols: Internet Protocol, Transmission control protocol, flow control,
  • QoS in today's Internet: Traffic management, TCP flow control, slow start, congestion avoidance;
  • End-to-end traffic control enhancements: TCP flavours (new Reno, SACK, ...)
  • Router based traffic control: random early drop (RED), FRED, ECN,
  • More Advanced router supported traffic control: Fair queueing.
  • QoS in future IP networks: Integrated services (IntServ), Service classes, RSVP, Admission control, traffic control and scheduling.
  • Differentiated services model (DiffServ), Architecture, service classes, ...
  • Topics on Quality of service in Wireless Internet
  • TCP in wireless environment: issues and challenges.
  • Link layer support for QoS in wireless networks: scheduling in wireless LAN.
  • Quality of service in future Wireless Internet: mobile ad-hoc networks.

Text Book:

Assorted textbooks and mostly reference materials

Reference Books/materials:

Grading Scheme: (tentative)

  • 2 midterms (50%)
  • Final presentation (20%)
  • A survey paper (30%)

Pre-requisites/Background needed:

Basic networking background/terminology

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: Permission of the Instructor

Course code: COMP670K

Course title: Topics in Theory: Online Algorithms

Instructor: Rudolf Fleischer

Room:

Telephone:

Email:

WWW page:

Area in which course can be counted: Theory

Course Description:

An online algorithm is an approximation algorithm with the additional handicap that it learns its input piecewise, and on getting some piece of input it must immediately decide on some part of the output not knowing what will come later. Typical online problems are buying stocks, organizing a fast processor cache, or scheduling jobs.

Course Objectives:

In this course we will learn how to measure the quality of online algorithms using competitive analysis.

Course Outline/Contents:

We will discuss the following problems: Exploration and navigation problems on graphs and in the plane, the k-server problem, the list update problem, splay trees, the money exchange problem, paging, graph coloring, and scheduling.

Text Book: No textbook.

Reference Books/materials:

  • A. Borodin, R. El-Yaniv: Online Computation and Competitive Analysis. Cambridge, 1998.
  • A. Fiat, G. Woeginger: Online Algorithms - The State of the Art. Springer, LNCS 1442, 1998.

Grading Scheme: TBA

Pre-requisites/Background needed: COMP271 or equivalent

Available for final year UG students to enroll: yes

Minimum CGA required for UG students: Permission of Instructor

Course code: COMP538

Course title: Reasoning and Decision under Uncertainty

Instructor: Nevin L. Zhang

Room: 3504

Telephone: x7015

Email:

WWW page: http://cse.hkust.edu.hk/~lzhang/

Area in which course can be counted: AI

Course Description:

AI methods of reasoning and decision under uncertainty. Probability theory and Bayesian networks. Bayesian decision theory and influence diagrams. Markov decision processes and planning under uncertainty. Learning with Bayesian networks. Other approaches. Applications.

Course Objectives:

Bring students up to date about probabilistic approaches in AI.

Course Outline/Contents:

(VERY TENTATIVE)

  • Probability basics.
  • Probabilistic inference and Bayesian networks
    • Basic concepts.
    • Inference algorithms.
    • Applications and softwares.
    • Error-correcting codes.
  • Learning in Bayesian networks.
    • Parameter learning/EM algorithm
    • Hidden Markov models and applications in speech (Guest lecture?)
    • Structure learning
    • Applications in information retrieval (Guest Lecture)
    • Factor analysis and latent class analysis and their potential applications to Chinese medicine
  • Decision theory and influence diagrams
  • Markov decision processes and planning
    • Value iteration and policy iteration
    • Classic planning (Guest lecture?)
    • Reinforcement learning (Guest lecture?)
    • Dynamic Bayesian networks
    • Partially observable Markov decision processes

Text Book:

Reference Books/materials: The course will be based on research papers.

Grading Scheme: To be determined.

Pre-requisites/Background needed:

PG status. Background in Probability theory and Statistics will help.

Available for final year UG students to enroll: No

Minimum CGA required for UG students: N/A

Course code: COMP641E

Course title: Topics in Graphics: Geometric Modeling

Instructor: Chiew-Lan Tai

Room: 3515

Telephone: x7020

Email:

WWW page: cse.hkust.edu.hk/~taicl/

Area in which course can be counted: ST

Course Description:

Geometric modeling is an important topic in computer graphics and computer-aided design. To obtain different views of a object -- static or moving, rigid or deformable -- using standard graphics rendering techniques, we first have to create a three-dimensional geometric model of the object. This course will cover both classical approaches, such as Bezier and B-spline surfaces, and the more recent approaches based on subdivison surfaces. Both the underlying mathematical theory and its implementation in terms of efficient algorithms will be taught.

Course Objective:

This course aims to provide the students with a good understanding of the characteristics of various geometric modeling techniques so that they can select a representation that best suits the needs of an application.

Course Outline/Contents:

  • Bezier, B-spline and NURBS curves and surfaces
  • B-spline knot insertion/removal, degree reduction/elevation
  • Implicit surfaces
  • Solid modeling
  • Subdivision surfaces
  • Polygonal mesh models

Text Book: none

Reference Books/materials:

The NURBS book, L. Piegl and W. Tiller, Springer-Verlag. ISBN: 3-540-61545-8, 1997

Grading Scheme:

  • Assignments: 30%
  • Midterm: 30%
  • Course project: 40%

Pre-requisites/Background needed: Linear algebra; basic computer graphics

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: B+

Course code: COMP630D

Course title: Topics in Database Systems: Internet and mobile database systems

Instructor: Dik Lee

Room: TBD

Telephone: x7017

Email:

WWW page: http://cse.hkust.edu.hk/~dlee

Area in which course can be counted: DB

Course description (can be more detailed than the one in the calendar):

Topics in data management and dissemination on internet, including data extraction, integration, indexing, searching, clustering, and interface; data management issues on wireless networks.

Course objective:

  1. broad knowledge in data management issues on internet and wireless networks
  2. develop indepth knowledge in a specific topic by carrying out a course project

Course outline/content (by major topics):

  • data management on internet
  • data extraction and representation
  • search on internet
  • semantic clustering
  • data access on wireless network
  • broadcast and on-demand services
  • indexing and caching
  • pervasive computing issues

Text book: None.

Reference books/materials: TBA

Grading Scheme:

course project and class presentations

Pre-requisites/Background needed: CS UG background

Available for final year UG students to enroll: No.

Minimun CGA required for UG students: N/A

Course code: COMP630C

Course title: Spatial, Image and Multimedia Databases

Instructor: Dr. Dimitris Papadias

Telephone: x6971

Email:

WWW page: http://cse.hkust.edu.hk/~dimitris

Area in which course can be counted: DB

Course description:

Introduction to Spatial Databases and Geographic Information Systems. Image Querying by Content. Spatial Access Methods. Pictorial Query Languages. Spatial Reasoning and Constraint Satisfaction. Multi-dimensional Query Processing.

Course objective:

The objective of the course is to provide an overview of the recent trends in Spatial Databases and related fields including Geographic Information Systems, Image and Multimedia Databases. The classes will be split in two types: in the first type the instructor will cover a research area topic by giving a general overview. In the subsequent classes students will be required to give presentations on specialized topics of the area. This will encourage students' participation, increase their depth of knowledge in the the field and enhance their presentation skills. The instructor will assist students to prepare and present the material.

Organization - Grading Scheme

The class will be split in 10 groups each responsible for a specific topic. Each member of a group will give a presentation on the topic which will count for 25% of his mark. Before its first presentation each group (except for groups 1 and 2) will distribute to the class a survey paper on the topic of its interest (co-authored by all members). This will account for 25% of every member's grade. The paper will be graded by all other groups and the instructor based on the search of literature, clarity etc. At the end of the semester all students must submit an (implementation) project. Students will be organized in teams which may be different from the original presentation groups. The project will 30% of the grade. In order to enhance participation, there will be a final Quiz. The reading material for the Quiz will be the survey papers of all groups. This will account for 20% of the grade.

Available for final year UG students to enroll: yes

Minimum CGA required for UG students: Permission of Instructor

Archive of past courses