Now suppose that you want your parameter to be e-close to the optimal one, i.e., you want — 5 e. How many itaations do you need to on the algorithm to guarantee this?Explain.
Neural Networks Suppose we are given data where xi E Rd, . E R, E R”h and wt e Rh and a 0’s the sigmoid function) Let us consider the following non, network objective function. (w. • w2) = t(a — wi c(lq xal)2 • • What is the gradient of this function? • the […]