**CS 550
Machine Learning
**

**Description:**
Overview of Machine Learning. Concept Learning. Version
Spaces. Inductive Bias. Induction of Decision Trees, overfitting,
pruning. Evaluating Hypotheses. Bayesian Learning, Bayes Optimal
Classifier, Naive Bayes Classifier, Bayesian Networks. Computational
Learning Theory. Instance-Based Learning, *k*-Nearest Neighbor
Learning, Locally Weighted Linear Regression. Genetic Algorithms,
Genetic Programming. Learning Sets of Rules. Analytical
Learning. Reinforcement Learning. Feature Projections Based
Approaches. *Credit units: 3*.

**Semester: Spring 2005**
**Schedule:** Monday 11:40 - 12:30; Thursday 13:40 - 15:30
**Office Hours:** Wednesday 15:40 - 17:40
**Classroom:** EA-502
**Instructor:** H. Altay Güvenir

**Main Text Book:**

Tom M. Mitchell, *Machine Learning*, McGraw-Hill, 1997.

**Recommended Text Book:**

Pat Langley, *Elements of Machine Learning*, Morgan Kaufmann, 1996.

**Recommended Journals:**

*Machine Learning*,
*Journal of Machine Learning Research*,
*Artificial Intelligence*,
*Journal of Artificial Intelligence Research*,
*IEEE Transactions on Pattern Analysis and Machine Intelligence*.
*Knowledge-Based Systems*

**
Weekly Schedule**

WEEK DAYS TOPICS1 Feb. 3 Overview of Machine Learning, Concept Learning 2 Feb. 7, Feb. 10 Concept Learning Version Spaces 3 Feb. 14, Feb. 17 Decision Tree Learning, Evaluating Hypotheses 4 Feb. 21, Feb. 24 Bayesian Learning, Naive Bayesian Learning 5 Feb. 28, Mar. 3 Instance-Based Learning 6 Mar. 7, Mar. 10 Genetic Algorithms 7 Mar. 14, Mar. 17 Seminar 8 Mar. 21, Mar. 24 Seminar 9 Mar. 28, Mar. 31 Seminar 10 Apr. 4, Apr. 7 Seminar 11 Apr. 11, Apr. 14 Spring Break 12 Apr. 18, Apr. 21 Seminar 13 Apr. 25, Apr. 28 Workshop 14 May 2, May 5 Workshop 15 May 9, May 12 Workshop 16 May 16 Workshop

**Seminar: Presentation:**
Each student will present a journal paper, or a small set of conference papers preferably written
by the same group of authors on the same topic. Students are free to select
the paper(s) they would like to present as long as they are in the scope
of the course and approved by the instructor.
Students will determine and submit, by email, the link to, or a hard copy of the paper(s)
they will present to the instructor by **March 1, 2005**.
The complete schedule of the presentations will be announced on March 3, 2005.
Each student will have 20 mins. to present his/her paper.
We will have a 5 min. discussion period after each presentation.
Those who will present paper(s) that are available only on hard copies are responsible for
providing the other classmates with copies of their paper(s) in a week advance.

Students are referred to the paper "How to Present a Paper in Theoretical Computer Science: A Speaker's Guide for Students" for a successful presentation.

**Seminar: Participation:**
Other than his/her presentation, each student is expected to read the
papers to be presented by others before the presentation.
After each presentation, we will have a discussion session.
Each student will be graded in his/her participation to the seminar.

**Workshop:**
We will organize a workshop during the last weeks of the semester.
Each student will conduct an experiment, testing new ideas preferably
on the area of their presentation topic.
Then each student will prepare a short paper,
reporting his/her experiment(s) along with the interpretation of the
results and pointers for further research.
The papers must be in the range of 8-10 pages long, in 11 point Times New Roman font.
The paper should have the quality of, at least, a national symposium paper.
PDF versions of the papers will be submitted to the instructor by **April 7, 2005**.
Each paper will be reviewed by two randomly selected classmates.
The papers will be emailed for reviewing on April 8, 2005.
Each reviewer will put his/her comments and suggestions on the paper
and return them back to the instructor by **April 18, 2005**.
The papers with peer reviews will then be
returned to the authors on April 22, 2005.
The workshop will start on **April 25** at 14:40
and finish on **May 16, 2005**.
Each student will have 15 min. to present his/her paper.
The authors will revise, if necessary, their papers
in the light of the reviews and discussions during the presentations, and
submit the final copies by **May 20, 2005** to the instructor, in PDF format.

Students are referred to the paper "Howto give a good research talk" for a successful presentation of your own work.

**Grading Policy:**

Seminar: 40% (Presentation: 30% + Participation: 10%) Workshop: 60% (Presentation: 10% + Review: 10% + Paper: 40% )

**On-line information:**

- General Guidelines for Term Project Paper Review
- Paper Review Form
- UCI Machine Learning Repository
- Bilkent University Function Approximation Repository
- Weka: Machine Learning Software in Java
- Programs
- Grades

Click here to send an email to whole class