Stationary memoryless sources produce two correlated random sequences $X^n$ and $Y^n$. A guesser seeks to recover $X^n$ in two stages, by first guessing $Y^n$ and then $X^n$. The contributions of this work are twofold: (1) We characterize the least achievable exponential growth rate (in $n$) of any positive $\rho$-th moment of the total number of guesses when $Y^n$ is obtained by applying a deterministic function $f$ component-wise to $X^n$. We prove that, depending on $f$, the least exponential growth rate in the two-stage setup is lower than when guessing $X^n$ directly. We further propose a simple Huffman code-based construction of a function $f$ that is a viable candidate for the minimization of the least exponential growth rate in the two-stage guessing setup. (2) We characterize the least achievable exponential growth rate of the $\rho$-th moment of the total number of guesses required to recover $X^n$ when Stage 1 need not end with a correct guess of $Y^n$ and without assumptions on the stationary memoryless sources producing $X^n$ and $Y^n$.

翻译：没有固定内存的源源产生两个相关的随机序列美元和美元。一个猜测者试图在两个阶段中收回美元,先猜测美元,然后假设美元,然后假设美元,然后美元。这项工作的贡献是双重的:(1) 我们将任何正值美元(美元)的最小指数增长率(单位为美元)确定为每千元总数第一刻,而美元是通过确定性功能获得的。 我们证明,根据美元,两阶段设置中最小的指数增长率低于美元,这取决于美元,在两阶段设置中,以美元直接猜算时,以美元为单位。我们进一步建议简单哈夫曼代码构建一个功能,以美元为单位,这是将两阶段假设中最小的指数增长率最小化的一个可行选择。 (2) 我们确定,在第一阶段需要的不是美元时,以美元为单位,以美元为单位,以美元为单位,以美元为单位,以美元为单位,以美元为单位,以最小的指数增长率最低。