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We prove a separation between offline and online algorithms for finger-based tournament heaps undergoing key modifications. These heaps are implemented by binary trees with keys stored on leaves, and intermediate nodes tracking the min of their respective subtrees. They represent a natural starting point for studying self-adjusting heaps due to the need to access the root-to-leaf path upon modifications. We combine previous studies on the competitive ratios of unordered binary search trees by [Fredman WADS2011] and on order-by-next request by [Martinez-Roura TCS2000] and [Munro ESA2000] to show that for any number of fingers, tournament heaps cannot handle a sequence of modify-key operations with competitive ratio in $o(sqrt{log{n}})$. Critical to this analysis is the characterization of the modifications that a heap can undergo upon an access. There are $exp(Theta(n log{n}))$ valid heaps on $n$ keys, but only $exp(Theta(n))$ binary search trees. We parameterize the modification power through the well-studied concept of fingers: additional pointers the data structure can manipulate arbitrarily. Here we demonstrate that fingers can be significantly more powerful than servers moving on a static tree by showing that access to $k$ fingers allow an offline algorithm to handle any access sequence with amortized cost $O(log_{k}(n) + 2^{lg^{*}n})$.
In FOCS 1986, Wilber proposed two combinatorial lower bounds on the operational cost of any binary search tree (BST) for a given access sequence $X in [n]^m$. Both bounds play a central role in the ongoing pursuit of the dynamic optimality conjecture
In this paper we present a new data structure for double ended priority queue, called min-max fine heap, which combines the techniques used in fine heap and traditional min-max heap. The standard operations on this proposed structure are also present
With an exploding global market and the recent introduction of online cash prize tournaments, fantasy sports contests are quickly becoming a central part of the social gaming and sports industries. For sports fans and online media companies, fantasy
We show the $O(log n)$ time extract minimum function of efficient priority queues can be generalized to the extraction of the $k$ smallest elements in $O(k log(n/k))$ time, where we define $log(x)$ as $max(log_2(x), 1)$. We first show heap-ordered tr
In the classic Integer Programming (IP) problem, the objective is to decide whether, for a given $m times n$ matrix $A$ and an $m$-vector $b=(b_1,dots, b_m)$, there is a non-negative integer $n$-vector $x$ such that $Ax=b$. Solving (IP) is an importa