CS 473/573 - Algorithms I


Semester:     Spring, 2018-2019
Text Book:   T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Mit Press and McGraw-Hill, 2009.
Instructors:Ugur Dogrusoz and Mustafa Ozdal
Assistants:   M. Ozan Karsavuran (EA505), Nabil Abubaker (EA505), Gunduz Vehbi Demirci (EA505)
Syllabus:     2019SPRING-Syllabus

Lecture Hours:
Section 1: Classroom: BZ-02  Wednesday 09:40-10:30,  Friday 10:40-12:30
Section 2: Classroom: EE-214  Tuesday 10:40-12:30,  Friday 09:40-10:30

Office Hours:
Ugur Dogrusoz: Wednesday 08:30-09:30 Weekly Schedule
Mustafa Ozdal: Tuesday 15:40-16:30
Ozan Karsavuan: Wednesday 13:30-14:30
Nabil Abubaker: TBA
Gunduz Demirci: TBA


Check this page regularly for announcements.

Exams:
Midweek exams are open books, closed notes/slides.
Midterm and final exams are closed books/slides.

Tentative exams dates:
MWE1: February 25
MWE2: March 11
MT: March 27
MWE3: April 8
MWE4: April 17
MWE5: April 29
MWE6: May 9
Final: TBA

Midterm: March 27, 17:40 - 19:40
Coverage: Lectures 1-8
Exam rooms according to last name:
EE-05: Aghazada - Feta
EE-03: Gani - Özer
EE-04: Özgürel - Zhumasheva

Midweek exam #2: March 11, 17:40 - 19:20
Coverage:
    Divide and Conquer Design Paradigm (Lecture 04)
    Quicksort (Lecture 05)
    Analysis of Quicksort (Lecture 06a)
    Randomized Quicksort (Lecture 06b)

Midweek Exam #1: February 25, 17:40 - 19:20
Coverage:
    Introduction to Analysis of Algorithms (Lecture 01)
    Asymptotic Notation (Lecture 02)
    Solving Recurrences (Lecture 03)


TOPICS & SLIDES
The lectures belonging to Ugur Dogrusoz are indicated by "UD".
The lectures belonging to Mustafa Ozdal are indicated by "MO".

Lecture UD MO

Lecture 01: Introduction: analysing algorithms, designing algorithms

(pdf) (pdf) (pptx)

Lecture 02: Asymptotic Notation

(pdf) (pdf) (pptx)

Lecture 03: Solving Recurrences

(pdf) (pdf) (pptx)

Lecture 04: Divide and Conquer Design Paradigm

(pdf) (pdf) (pptx)

Lecture 05: Quicksort

(pdf) (pdf) (pptx)

Lecture 06a: Analysis of Quicksort

(pdf) (pdf) (pptx)

Lecture 06b: Randomized Quicksort

(pdf) (pdf) (pptx)

Lecture 07: Medians and Order Statistics

(pdf) (pdf) (pptx)

Lecture 08: Heapsort

(pdf) (pdf) (pptx)

Lecture 09: Sorting in Linear Time

(pdf) (pdf) (pptx)

Lecture 10: Dynamic Programming

(pdf) (pdf) (pptx)

Lecture 11: Greedy Algorithms

(pdf) (pdf) (pptx)

Lecture 12a: Amortized Analysis

(pdf) (pdf) (pptx)

Lecture 12b: Dynamic Tables

(pdf) (pdf) (pptx)

Extra examples for dynamic programming

(pdf) (pptx)

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