Course Name: Randomized Methods in Complexity

Course abstract

In this course we will study how randomness helps in designing algorithms and how randomness can be removed from algorithms. We will start by formalizing computation in terms of algorithms and circuits. We will see an example of randomized algorithms-- identity testing --and prove that eliminating randomness would require proving hardness results. We prove hardness results for the problems of parity and clique using randomized methods. We construct `highly’-connected graphs called expanders that are useful in reducing randomness in algorithms. These lead to a surprising logarithmic-space algorithm for checking connectivity in graphs. We show that if there is hardness in nature then randomness cannot exist! This we prove by developing pseudo-random generators and error-correcting codes.


Course Instructor

Media Object

Prof. Nitin Saxena

I completed my Bachelors in Computer Science from the Indian Institute of Technology, Kanpur in 2002 and completed my PhD under Manindra Agrawal in 2006. I am broadly interested in Computational Complexity Theory, Algebra, Geometry and Number Theory. I have been a visiting graduate student in Princeton University (2003-2004) and National University of Singapore (2004-2005); a postdoc at CWI, Amsterdam (2006-2008) and a Bonn Junior Fellow (W2 Professor) at Hausdorff Center for Mathematics, Bonn (2008-2013). Since April 2013, I have a faculty position in the department of CSE, IIT Kanpur.
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jan-Apr 2021

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 Syllabus

 Enrollment : 18-Nov-2020 to 25-Jan-2021

 Exam registration : 15-Jan-2021 to 12-Mar-2021

 Exam Date : 25-Apr-2021

Enrolled

487

Registered

4

Certificate Eligible

1

Certified Category Count

Gold

0

Silver

0

Elite

0

Successfully completed

1

Participation

1

Success

Elite

Silver

Gold





Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Randomized Methods in Complexity - Toppers list

Enrollment Statistics

Total Enrollment: 487

Registration Statistics

Total Registration : 4

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.