Coin Flipping in Dynamic Programming Is Almost Useless

S. Jukna
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Abstract

We consider probabilistic circuits working over the real numbers and using arbitrary semialgebraic functions of bounded description complexity as gates. In particular, such circuits can use all arithmetic operations (+, −, ×, ÷), optimization operations (min and max), conditional branching (if-then-else), and many more. We show that probabilistic circuits using any of these operations as gates can be simulated by deterministic circuits with only about a quadratical blowup in size. A slightly larger blowup in circuit size is also shown when derandomizing approximating circuits. The algorithmic consequence, motivating the title, is that randomness cannot substantially speed up dynamic programming algorithms.
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动态规划中的抛硬币几乎毫无用处
我们考虑工作在实数上的概率电路,并使用有界描述复杂度的任意半代数函数作为门。特别是,这样的电路可以使用所有的算术运算(+,−,x, ÷),优化运算(最小和最大),条件分支(if-then-else)等等。我们证明,使用这些操作中的任何一种作为门的概率电路都可以用确定性电路模拟,其大小只有大约二次放大。当非随机化近似电路时,电路尺寸也会略微增大。这一算法的结果是,随机性不能大大加快动态规划算法的速度。
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