BARC/EADS Talk by Uri Zwick – Københavns Universitet

Selection from heaps, row-sorted matrices and $X+Y$ using soft heaps
We use soft heaps to obtain simpler optimal algorithms for selecting the $k$-th smallest item, and the set of~$k$ smallest items, from a heap-ordered tree, from a collection of sorted lists, and from $X+Y$, where $X$ and $Y$ are two unsorted sets.
Our results match, and in some ways extend and improve, classical results of Frederickson (1993) and Frederickson and Johnson (1982). In particular, for selecting the $k$-th smallest item, or the set of~$k$ smallest items, from a collection of~$m$ sorted lists
we obtain a new optimal \emph{output-sensitive"} algorithm that performs only $O(m+\sum_{i=1}^m \log(k_i+1))$ comparisons, where $k_i$ is the number of items of the $i$-th list that belong to the overall set of~$k$ smallest items.