CSN-501: Advanced Algorithms
(Autumn 2017-2018)

M. Tech. (CSE) I Year, B. Tech. (CSE) IV Year, PhD

Course Instructor: Sudip Roy

Teaching Assistants: Ankur Gupta (PhD Student), Sumit Sharma (PhD Student), Debasis Gountia (PhD Student), Kanishk Lohumi (MTech II Year Student), Arjun Sharma (MTech II Year Student)

 

Course Outline

• This is a course of Four (4) credit.
• It consists of Three (3) lecture hours per week and One (1) hour tutorial.
  
• The basic thrust of the course would be to familiarize the students with the design and analysis of efficient algorithms. Its goal is to make students familiar with the important algorithm design techniques for solving problems. Several algorithmic design paradigms will be discussed as follows: Brute force, Greedy algorithms, Divide-and-conquer, Dynamic programming, Graph Algorithms, Backtracking and branch-and-bound, Evolutionary Algorithms: GA, SA, PSO, ACO, TS, etc., Geometric Algorithms, Approximation Algorithms, Randomized Algorithms, Parallel Algorithms.
• We will try to stick to the basic course outline as given in Syllabus, but may deviate a bit.
  
• Prerequisite: Nil.
• Performance Evaluation: Class Work Sessional (CWS) = 25%, Mid-Term Exam (MTE) = 25%, End-Term Exam (ETE) = 50%.
• CWS (25% marks) will be computed by a weighted sum of different components.

 

General Information

• This is a core course for M.Tech. (CSE) I year, BTech (CSE) IV year and PhD students (Total Strength: ~45).

• Lecture Class Timings:
  Mondays: 12 noon - 1 pm, Wednesdays: 12 noon - 1 pm and Fridays: 12 noon - 1 pm
  Lecture Venue: W-201, Dept. of CSE

• Tutorial Class Timings:
  Batch-I: Fridays (2 - 3 pm), Venue: W-201, Dept. of CSE
  Batch-I: Fridays (3 - 4 pm), Venue: W-201, Dept. of CSE

• Course Web-page: http://faculty.iitr.ac.in/~sudiproy.fcs/courses/csn501_2017.html

• Piazza Course Site: https://piazza.com/iitr.ac.in/fall2017/csn501/

• Moodle site: https://moodle.iitr.ac.in/course/view.php?id=29

• Office time to meet the Course Instructor (For any kind of doubt clearing): Monday - Friday (5:00 pm - 6:00 pm)
  (To confirm the availability, please send an email before coming)

 

Study Materials

Books:
[B1] M. H. Alsuwaiyel, “Algorithms Design Techniques and Analysis”, World Scientific Publishing, 2016.
[B2] Jon Kleinberg and Éva Tardos, Algorithm Design, Pearson, 2005.
[B3] Anany Levitin, Introduction to The Design and Analysis of Algorithm, III edition, Pearson, 2011.
[B4] (JOR) Joseph O'Rourke, Computational Geometry in C, Cambridge University Press.
[B5] (Four Authors) M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf, Computational Geometry: Algorithms and Applications (2nd Edition), Springer-Verlag.

References:
[R1] Thomas H. Cormen, Charles E. Lieserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, Second Edition, MIT Press/McGraw-Hill, 2009.
[R2] Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani, “Algorithms”, Tata McGraw-Hill. 2008.
[R3] Lecture notes by Prof. David Mount, Department of Computer Science, University of Maryland, USA.
[R4] Lecture notes by Prof. Sandeep Sen, Department of Computer Science & Engineering, Indian Institute of Technology Delhi, India.
[R5] Lecture notes by Prof. David Mount, Department of Computer Science, University of Maryland, USA.

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Last updated on: 25 August, 2017
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