  The saturation effect refers to the phenomenon that the kernel ridge
regression (KRR) fails to achieve the information theoretical lower bound when
the smoothness of the underground truth function exceeds certain level. The
saturation effect has been widely observed in practices and a saturation lower
bound of KRR has been conjectured for decades. In this paper, we provide a
proof of this long-standing conjecture.
