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Clarify on Assignment-1 Matlab Functions and Tools • Some functions are given. There is no need to implement them. Please refer to the links in the next slide. • You can also use other resources, with proper citation in your report. Useful Matlab Functions • Naïve Bayes classifier – PredictClass = classify(Xtest,Xtrain,Ytrain,’diaglinear’); • Randomly split

Homework 8 Due April 7, 2017 at 11:59 p.m. There are 5 time slots that you can utilize to transmit the data. You may transmit the data quickly using just one time slot or you may transmit the data slower using all 5 time slots or any number of time slots between 1 and 5.

% Use ipdriver to solve % % min c’x subject to A*x=b, x>=0, % A = [1 1 -1 0; 3 1 0 -1]; b = [3 6]’; c = [2 1 0 0]’; [x,y,s] = ipdriver(c,A,b); %load AFIRO etc… % Example AFIRO from Netlib. % % Netlib [1] provide a set of linear programming

%Replicate in Matlab the computations performed in Problem 4 of Workshop 1. %0 %Define: % A = eye(6); f = [1, 1, 1, 1, 1, 2]’; BarA = A + f*f’ %should give % %BarA = % % 2 1 1 1 1 2 % 1 2 1 1 1 2 % 1 1 2

% % Exercise 2: % % Consider the following LP: % % min x_1 + 3 x_2 % s.t. x_1 + x_2 = 1 % x_i >= 0, i = 1, 2. % % Formulate the first order optimality condition for the barrier problem: % % x_1 + x_2 = 1 % y + s_1

function NS = newtonsolver(A,x,s) %NEWTONSOLVER Prepare linear solver for Newton system. % % NS = newtonsolver(A,x,s) returns a MATLAB struct that holds the % factorization of the Newton matrix for solving the step equations in % the IPM. [m n] = size(A); NS = struct(); % Factorization Method % ——————– % 1: augmented system, LU