Learning Objectives
This course concentrates on recognizing and solving convex optimization problems that arise in applications.
Learning outcome
At the end of the course student will be able to define appropriate optimization problem for a given practical problem. Student will be able to implement code and solve an optimization problem using MATLAB and CVX.
Syllabus
*INTRODUCTION * : convex sets, functions , basics of convex analysis, [2 lectures]
RELEVANT OPTIMIZATION CONCEPTS AND METHODS : Constrained vs. unconstrained; QP, LP and NLP , Combinatorial, Stochastic and Semidefinite optimization algorithms; MinMax algorithms; Extreme point analysis, saddle point method. Chance constrained program. (8 lectures)
UNCONSTRAINED OPTIMIZATION AND MULTIDIMENSIONAL GRADIENT METHODS: SteepestDescent, ConjugateGradient, Newton, QuasiNewton, SubGradient, (4 lectures)
Few Selected Topics from following list : (4 lectures) Stochastic Gradient descent, Proximal methods, Accelerated Proximal methods, ADMM, convex optimization for big data, interiorpoint methods;
CONSTRAINED OPTIMIZATION: Lagrange Multiplier, Karush Kuhn Tucker (KKT) conditions, FirstOrder and SecondOrder Necessary Conditions for minima and maxima; (4 lectures)
Few Selected Topics from following list : (4 lectures) Duality Theory. Project Gradient, L*norms; Multiple kernel Method, penalty barrier methods
APPLICATION : signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design and finance. (4 lectures)
Text books

Convex Optimization, Stephen Boyd and Lieven Vandenberghe Paperback Cambridge India (2016) ISBN13: 9781316603598/1316603598

Practical Methods of Optimization 2nd Edition Paperback , Wiley India (2017) ISBN13: 9788126567904/8126567902
#Refferenes

Convex Optimization Theory, 1st Edition, Dimitri P. Bertsek , Paperback Universities Press, @2010, ISBN13: : 9788173717147/ 8173717141

Convex Optimization Algorithm, 1st Edition, Dimitri P. Bertsek , Universities Press, @2010, ISBN13: 9781886529281/ 1886529280
Meta Data
 Proposing Faculty : Dr Sahely Bhadra
 Department / Centre : Computer Science and Engineering
 Programme : B.Tech
 Proposal Type: Old
 Offerings