2019
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds
NeurIPS 2019spotlight
A crucial assumption in most statistical learning theory is that samples are independently and identically distributed (i.i.d.). However, for many real applications, the i.i.d. assumption does not hold. We consider learning problems in which examples are dependent and their dependency relation is ch…