Hello,

I am doing something like the following but that runs the optimizer several times, which is slow.

```
for i = 1:nDimY
cvx_begin quiet
variables W_y(nDimY) W_x(nDimX)
minimize (norm(W_y'*trout - W_x'*trin,2))
subject to
W_y(i) == 1
cvx_end
end
```

Result is the minimum of the loop. Assuming that 0 <= W_y(i) <=1 then I can write

```
subject to
norm(W_y,Inf) == 1
```

as a convex optimization task

but that constraint is not allowed. Can I reword this constraint in a way CVX will appreciate?

Thanks