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group_ADMM.m
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group_ADMM.m
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function [obj_GADMM, loss_GADMM, Iter]=group_ADMM(XX,YY, rho, no_workers, num_feature, noSamples, num_iter, obj0, acc)
Iter= num_iter;
s1=num_feature;
s2=noSamples;
lambda = zeros(s1,no_workers);
out=zeros(s1,no_workers);
max_iter = num_iter;
for i = 1:max_iter
for ii =1:2:no_workers
cvx_begin quiet
%cvx_precision high
%cvx_solver mosek%SDPT3 %mosek
variable x(s1)
if ii==1
C1 = zeros(s1,1);
term_1 =0;
else
C1= lambda(:,ii-1);
term_1=rho/2*sum_square(x-out(:,ii-1));
end
if ii == no_workers
C2 = zeros(s1,1);
term_2 = 0;
else
C2= lambda(:,ii);
term_2 = rho/2*sum_square(x-out(:,ii+1));
end
first = (ii-1)*s2+1;
last = first+s2-1;
%cvx_solver mosek
minimize(0.5*sum_square(XX(first:last,1:s1)*x - YY(first:last))- C1'*x+C2'*x + term_1...
+term_2)
cvx_end
out(:,ii) =x;
end
for ii =2:2:no_workers
cvx_begin quiet
%cvx_precision high
%cvx_solver mosek%SDPT3 %mosek
variable x(s1)
C1= lambda(:,ii-1);
if ii == no_workers
C2 = zeros(s1,1);
term_2 = 0;
else
C2= lambda(:,ii);
term_2 = rho/2*sum_square(x-out(:,ii+1));
end
term_1=rho/2*sum_square(x-out(:,ii-1));
first = (ii-1)*s2+1;
last = first+s2-1;
minimize(0.5*sum_square(XX(first:last,1:s1)*x - YY(first:last))- C1'*x+C2'*x + term_1...
+term_2)
cvx_end
out(:,ii) =x;
end
for ii=1:no_workers-1
lambda(:,ii) = lambda(:,ii) + rho*(out(:,ii)-out(:,ii+1));
end
final_obj = 0;
for ii =1:no_workers
first = (ii-1)*s2+1;
last = first+s2-1;
final_obj = final_obj + 0.5*sum_square(XX(first:last,1:s1)*out(:,ii) - YY(first:last));
end
obj_GADMM(i)=final_obj;
loss_GADMM(i)=abs(final_obj-obj0);
if(loss_GADMM(i) < acc)
Iter = i;
break;
end
end