Error on minimizing matrix through fmincon and quadprog :(

I'm currently in the process of minimizing a skewness coskewness matrix to find the optimal weight of an asset class.

With fmincon i get the error; User supplied objective function must return a scalar value.

With quadprog i get the error; The Hessian must have the same number of rows and columns

I've got 8 asset classes, so when minimizing the var/covar matrix i had no issue through the fmincon/quadprog function since its 8x8 matrix.

However, the skewness coskewness matrix is 8 * 64 matrix My data matrix is 145*8 matrix (where i put my returns).

Data = is a 145*8 matrix
skew_coskew = 8 * 64 matrix
A = ones(1,8)
S = cov(Data)*12

%initial weights
x0=zeros(1,size(Data,2))';

%optimization settings algorithmn
Aeq=ones(1,8)
beq=1; 
optimopt = optimset('fmincon'); 
optimopt = optimset('algorithm','interior-point')
optimopt.MaxIter=500000;    
optimopt.MaxFunEvals=50000;

%minimizing through fmincon
%[weights,fval,exitflag] = fmincon(@(X)  skew_coskew*-1,x0,[],[],Aeq,beq,zeros(8,1),ones(8,1),[],optimopt);

%minimizing through quadprog
[weights,fval,exitflag,output]=quadprog(skew_coskew*-1,zeros(8,1),[],[],Aeq,beq,zeros(8,1),ones(8,1),[]);

The question I have, is there any way to find an optimal maximum for my weights vector of this skew-coskewness matrix? It seems to me I can't use these functions since my skewn coskew matrix will ofc. always have other dimensions.