Topics in computer and information science

2022/2023
Programme:
Computer Science and Mathematics, Second Cycle
Year:
1 ali 2 year
Semester:
first
Kind:
optional
ECTS:
6
Language:
slovenian, english
Course director:

Zoran Bosnić

Lecturer (contact person):

Jure Leskovec

Hours per week – 1. semester:
Lectures
3
Seminar
0
Tutorial
2
Lab
0
Prerequisites

There are no prerequisites.

Content (Syllabus outline)

The course is intented for established visiting researchers and lecturers and for experts in computer and information science which will introduce students to topics that are interesting due to recent theoretical findings and mehodological breakthroughs or for their applicative value, and are as such not included into the existing curriculum.
The specific contents of the course is determined yearly.

Readings

Thomas H. Cormen, Charles E. Leiserson…: Introduction to Algorithms, 2nd edition, MIT Press, 2001.
Graham, Ronald L., Knuth, Donald E., Patashnik, Oren (1994). Concrete Mathematics (second ed.). Reading, MA: Addison-Wesley Publishing Company. pp. xiv+657. ISBN 0-201-55802-5. MR1397498
O'Regan, Gerard: A Brief History of Computing, Springer, 2008.
Dodatna literatura se predpiše vsako leto posebej glede na vsebino in predloge izbranega predavatelja.
Additional literature is given yearly, with respect to the current topic of the course.

Objectives and competences

The goal of the course is to introduce basic theoretical ideas as well as practical implementations of new methods and technologies in the field of computer and information science

Intended learning outcomes

After the completion of the course a student will:

-obtain a broader overview and understanding of the field of study, and of up to date methods and
concepts,

-apply current approaches and techniques from the specific field of computer and information science,
-understand the advantages of the chosen approaches in computer and information science in
solving specific practical tasks,

-solve complex problems, design complex systems.

Learning and teaching methods

Lectures, lab excersises

Assessment

Continuing (homework, midterm exams, project work)
Final (written and oral exam)
grading: 5 (fail), 6-10 (pass) (according to the Statute of UL)

Lecturer's references

OCEPEK, Uroš, RUGELJ, Jože, BOSNIĆ, Zoran. Improving matrix factorization recommendations for examples in cold start. Expert systems with applications, ISSN 0957-4174. [Print ed.], Nov. 2015, vol. 42, no. 19, str. 6784-6794, ilustr. [COBISS-SI-ID 1536335043]
BOSNIĆ, Zoran, KONONENKO, Igor. Estimation of individual prediction reliability using the local sensitivity analysis. Applied intelligence, ISSN 0924-669X. [Print ed.], Dec. 2008, vol. 29, no. 3, str. 187-203, ilustr. [COBISS-SI-ID 6174548]
BOSNIĆ, Zoran, KONONENKO, Igor. Comparison of approaches for estimating reliability of individual regression predictions. Data & Knowledge Engineering, ISSN 0169-023X. [Print ed.], Dec. 2008, vol. 67, no. 3, str. 504-516, ilustr. [COBISS-SI-ID 6923604]
BERDAJS, Jan, BOSNIĆ, Zoran. Extending applications using an advanced approach to DLL injection and API hooking. Software, ISSN 0038-0644, 2010, vol. 40, no. 7, str. 567-584. [COBISS-SI-ID 7694932]
BOSNIĆ, Zoran, KONONENKO, Igor. Automatic selection of reliability estimates for individual regression predictions. Knowledge engineering review, ISSN 0269-8889, 2010, vol. 25, no. 1, str. 27-47, graf. prikazi. [COBISS-SI-ID 7606356]