Lecture 12 - 2025 / 3 / 27

Balls and Bins (2)

Lemma:E\cal E 是关于 bin loads 的事件,且 Pr[E]\Pr[\cal E] 关于 mm 递增是单调上升 / 单调下降的,则 PrX[E]4PrY[E]\Pr_X[\mathcal E] \le 4 \Pr_Y[\mathcal E],其中 XX 为 Balls and Bins 模型,YYnn 个独立的 π(m/n)\pi(m/n)

不妨设 Pr[E]\Pr[\cal E] 单调上升,则

PrY[E]=k=0PrY[Ei=1nYi=k]Pr[i=1nYi=k]k=mPrY[Ei=1nYi=m]Pr[i=1nYi=k]PrY[Ei=1nYi=m]Pr[i=1nYim]PrX[E]14\begin{aligned} \Pr_Y[\mathcal E] & = \sum_{k=0}^{\infty} \Pr_Y\left[\mathcal E \mid \sum_{i=1}^{n} Y_i = k\right] \Pr\left[ \sum_{i=1}^{n} Y_i = k \right] \\ & \ge \sum_{k=m}^{\infty} \Pr_Y\left[\mathcal E \mid \sum_{i=1}^{n} Y_i = m\right] \Pr\left[ \sum_{i=1}^{n} Y_i = k \right]\\ & \ge \Pr_Y\left[\mathcal E \mid \sum_{i=1}^{n} Y_i = m\right] \Pr\left[ \sum_{i=1}^{n} Y_i \ge m \right]\\ & \ge \Pr_X [\mathcal E] \cdot \frac{1}{4} \end{aligned}

最后一步用到对于 λN\lambda \in \N,对于 Xπ(λ)X \sim \pi(\lambda),有 Pr[Xλ]1/4\Pr[X \ge \lambda] \ge 1/4

Corollary: Pr[i,Xic]4Pr[i,Yic]\Pr[\forall i, X_i \le c] \le 4 \Pr[\forall i, Y_i \le c]

TBD

Power of 2 Choices (1)

TBD