mvellon 
05052013 11:17 PM 
Q810: Problem parsing instructions
I understand how to generate and the data points in . I also know how to create permutations of these data points and that in each "epoch" of the algorithm I will want to visit each of the N points in a (newly) permuted data set. From here things get a little fuzzier. Each epoch will require a set of N "executions" of the SGD algorithm, running through all the points of its permuted data set. In each of these executions I start with the weight vector initialized to zeros. What do I do with the weight vectors resulting from SGD executions within an epoch? Do I average them? How do I terminate the SGD algorithm in the execution? Do I let it run for a prescribed number of iterations or do I terminate when the gradient gets small?
Most of my confusion stems from interpreting:
Run Logistic Regression with Stochastic Gradient Descent to find g and estimate Eout (the cross entropy error) by generating a sufficiently large separate set of points to evaluating the error. Repeat the experiment for 100 runs with different targets and take the average. The first part of it makes sense: run the experiment (multiple epochs) to get a final set of weights ( ) then generate a large set of points on which to evaluate the error. The second part, "Repeat the experiment for 100 runs with different targets and take the average", I find confusing. What "experiment"? The whole multipleepoch experiment? "With different targets"  does this mean different samples? Different permutations?
I fear I made a wrong turn in Albuquerque. Some clarification would be useful.
thanks
