CSC 7991- Seminar
in Neural Networks
Introduction to Neural Networks
0217 State Hall
Dr. Sorin Draghici
420 State Hall
hours: Tuesday 6pm-7.00pm, Thursday 6.00pm-7.00pm or by appointment
this web page you can find the syllabus, the transparencies used during
the course and announcements regarding the course if any.
Design - Martin T. Hagan, Howard B. Demuth, Mark Beale, 1995
Maps - Teuvo Kohonen, Second Edition, 1997
Circuit Complexity and Neural Networks - Ian Parberry, MIT Press, 1994
The course is intended for senior undergraduate and graduate students
interested in neural networks. The course may appeal to students with a
background in computer science, mathematics, physics or any engineering
field or to anybody interested in this particular topic.
are inspired by the way our brain works and they are one of the most powerful
machine learning techiques known to man to date. Neural network are able
to learn from examples without the need for an explicit understanding of
the phenomenon and without any programming. They can also generalize their
knowledge to exhibit proper behaviour in unseen cases, very similarly to
the way humans do. The range of applications for neural networks includes
pattern recognition, control, classsification, function approximation,
optimization, etc. The most advanced artifacts of modern technology today
-from electric razors to Ford automobiles- include neural networks
technology. This course is the follow-up for "Introduction to Neural Networks".
CSC785 - "Introduction to Neural Networks".
The students will
acquire specific knowledge about the field as well as general research
skills. The lectures will continue to present the most important neural
network paradigms and techniques with an emphasis to solving real world
problems. The course will discuss basic principles of research in general
and research in neural networks in particular. During the course, the students
will be required to undertake a project. The report for this project will
be the most important component of the grade and will be written in the
form of a research paper suitable for a technical publication. The actual
submission for publication of such paper is encouraged but not required.
contents - Class plan
In the first part,
the course will continue to cover several chapters from the indicated textbook.
Techniques not included in the textbook will be discussed. In the second
part of the course, students will present the results of their project
work. This project work will include reading research papers and presenting
them in class.
reserves the right to vary the level and depth of the material covered
in order to adapt the course to the background and level of the students.
Furthermore, some topics may be added if time permits.
all lectures is essential; the assignments, exams, etc. will be based primarily
(though not exclusively) on the materials presented in these lectures.
Also, assignments due dates, explanation and clarification of assignments
and material outside the textbooks will be presented during lecture
sessions. If you miss a lecture, it is your responsibility to obtain the
information covered in the session.
Please report to the instructor any health condition which may create a
classroom emergency (e.g. seizure disorders, diabetes, heart conditions,
lab: To enhance your learning and for your homework, the computer lab,
equipped with PC's and Unix workstations is available to you during the
time posted on the lab's door.
The grading will include a project in which the students will
demonstrate their understanding of the techniques presented, a classroom
presentation and a final exam. The report for the project will be
written as a research paper suitable for publication in a technical
journal or conference.
The final grade will
be calculated as follows:
Class discussion: 25%
Final exam: 15%
The final letter
grade will be determined approximately as follows:
A+: 95-100 %
F: less than 60%
A grade of Incomplete
(I) will not be given unless in very exceptional circumstances.
As a college student
who is committed to seek a higher education, we expect you be a very responsible
person. At the least, please:
Do your best to understand the material
covered in the class and ask questions when you do not understand.
Be aware of the homework assignments,
deadlines and late assignment policy.
Turn in your assignments in neat, readable
and easily accessible form.
Obtain notes and handouts from your
classmates if you miss a class for unavoidable circumstances.