SemesterFall Semester, 2020
DepartmentArtificial Intelligence, First Year Computer Science and Engineering, First Year
Course NameGraph Theory and Its Applications to Networks
InstructorKUO TUNG-WEI
Credit3.0
Course TypeElective
Prerequisite
Course Objective
Course Description
Course Schedule




























































































































































週次



課程主題



課程內容與指定閱讀



教學活動

與作業



學習投入時數

(課堂講授)



學習投入時數

(課堂前後)



1



Introduction (I)



TBA



TBA



3



2



2



Introduction (II)



TBA



TBA



3



2



3



Graphical Degree Sequence (I)



TBA



TBA



3



2



4



Graphical Degree Sequence (II)



TBA


TBA

3



2



5



Euler Tour



TBA



HW1



3



2



6



Midterm 1



N/A



N/A



N/A



2



7



Hamiltonian cycle (I)



TBA



TBA



3



2



8



Hamiltonian cycle (II)



TBA



TBA



3



2



9



Maximum Cardinality Matching (I)



TBA



TBA



3



2



10



Maximum Cardinality Matching (II)



TBA



TBA



3



2



11



Maximum Weighted Matching (I)



TBA



TBA



3



2



12



Maximum Weighted Matching (II)



TBA



HW2



3



2



13



Midterm 2



N/A



N/A



N/A



2



14



Network Flow and Linear Programming (I)



TBA



TBA



3



2



15



Network Flow and Linear Programming (II)



TBA



TBA



3



2



16



Network Flow and Linear Programming (III)



TBA



TBA



3



2



17



Graph Approximation Algorithm



TBA



HW3



3



2



18



Final



N/A



N/A



N/A



2




 


Teaching Methods
Teaching Assistant

TBA


Requirement/Grading

Midterm: 20%*2

Final: 20%

Homework: 10%*3

Class Participation: 10%



測驗藍圖

問答題10題

記憶: 10%

理解: 40%

應用: 10%

獨立思考: 40%



 


Textbook & Reference

TBA


Urls about Course
Attachment