A Time-Space Lower Bound for a Large Class of Learning Problems

We prove a general memory-samples lower bound that applies for a large class of learning problems and shows that for every problem in that class, any learning algorithm requires either a memory of quadratic size or an exponential number of samples. Our result is stated in terms of the norm of the matrix that corresponds to the learning pr...More