IST Mathematics for Computer Science (2018) - Speakers and Syllabus

The aim of this IST is to teach young mathematics and computer science teachers working in colleges and universities the mathematics behind many of the Algorithms in Computer Science. Starting with basic algorithms on graphs like minimum spanning trees, matchings and flows,  we hope to take participants to a point where they can be taught sophisticated algorithms which get used in machine learning like principal component analysis, clustering, random forests and page ranking. We will see the use of discrete mathematics in the design and analysis of algorithms on graphs and later see how linear algebra gets used in in convex optimization algorithms and many machine learning algorithms. Along the way we will introduce participants to the theory of NP completeness, linear programming and convex programming. Time permitting we may do more sophisticated algorithms for machine learning.

Syllabus to be covered in terms of modules of 6 lectures each

Name of the Speaker with affiliation, who will cover each module of 6 lectures.

No. of Lectures

Detailed Syllabus

Venkatesh Raman

3

Sorting, DFS, BFS, minimum spanning tree algorithms, matchings in bipartite graphs, analysis of algorithms

Meghana Nasre, IIT Madras

Prajakta Nimbhorkar, CMI

8

Network flows, reduction, NP completeness, TSP, vertex cover, integer programming

 

K V Subrahmanyam, CMI

4

Algorithms for rank, solving linear equations, linear programming, applications of LP,gradient descent, formulating convex programs, simple update algorithms.

Madhavan Mukund,

K V Subrahmanyam, CMI

9

Best fit subspaces, PCA, clustering, page ranking, SVD, Support vector machines, random forests.

 

References:

  1. Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, MIT Press/Prentice Hall India

  2. Algorithm Design, Jon Kleinberg and Eva Tardos, Pearson

  3. Foundations of Data Science, Arvim Blum, John Hopcroft, and Ravi Kannan

  4. Lecture notes, tutorials, and slides from the internet, as appropriate

 

Names of the tutors / course associate with their affiliation and status:

  1. K Sandesh Kamath, Research Scholar, CMI

  2. Muthuvel Murugan, Research Scholar, CMI

  3. Rajit Datta, Research Scholar, CMI

  4. Nada Pulath, IIT Madras

Tentative time-table:

 

Day

Date

Lecture 1

(9.30–11.00)

Tea

(11.00–11.30)

Lecture 2

(11.30–1.00)

Lunch

(1.00–2.30)

Tutorial 1

(2.30–3.30)

Tea

(3.30-4.00)

Tutorial 2

(4.00-5.00)

Tea & Snacks

5.00-5.30

 

 

name of the speaker

 

name of the speaker

 

name of the speaker/tutor

 

Name of the speaker/tutor)

 

Mon

18.6.2018

Raman

 

Prajakta

 

TBD

 

TBD

 

Tues

19.6.2018

Raman

 

Prajakta

 

TBD

 

TBD

 

Wed

20.6.2018

Raman

 

Meghana

 

 

 

 

 

Thu

21.6.2018

Meghana

 

Prajakta

 

 

 

 

 

Fri

22.6.2018

Meghana

 

Prajakta

 

 

 

 

 

Sat

23.6.2018

Meghana

 

KV

 

 

 

 

 

Sunday : Off

Mon

25.6.2018

KV

 

-

 

 

 

 

 

Tue

26.6.2018

KV

 

-

 

 

 

 

 

Wed

27.6.2018

KV

 

Madhavan

 

 

 

 

 

Thur

28.6.2018

KV

 

Madhavan

 

 

 

 

 

Fri

29.6.2018

KV

 

Madhavan

 

 

 

 

 

Sat

30.6.2018

KV

 

Madhavan