This article presents two new deterministic algorithms for constructing consensus trees. Given an input of phylogenetic trees with identical leaf label sets and leaves each, the first algorithm constructs the majority rule (+) consensus tree in time, which is optimal since the input size is , and the second one constructs the frequency difference consensus tree in time.

Our paper presents a new approach for temporal detection of human actions in long, untrimmed video sequences. We introduce Single-Stream Temporal Action Proposals (SST), a new effective and efficient deep architecture for the generation of temporal action proposals. Our network can run continuously in a single stream over very long input video sequences, without the need to divide input into short overlapping clips or temporal windows for batch processing. We demonstrate empirically that our model outperforms the state-of-the-art on the task of temporal action proposal generation, while achieving some of the fastest processing speeds in the literature. Finally, we demonstrate that using SST proposals in conjunction with existing action classifiers results in improved state-of-the-art temporal action detection performance.

A consensus tree is a single phylogenetic tree that summarizes the branching structure in a given set of conflicting phylogenetic trees. Many different types of consensus trees have been proposed in the literature; three of the most well-known and widely used ones are the majority rule consensus tree , the loose consensus tree , and the greedy consensus tree . This article presents new deterministic algorithms for constructing them that are faster than all the previously known ones. Given k phylogenetic trees with n leaves each and with identical leaf label sets, our algorithms run in O ( nk ) time (majority rule consensus tree), O ( nk ) time (loose consensus tree), and O ( n 2 k ) time (greedy consensus tree). Our algorithms for the majority rule consensus and the loose consensus trees are optimal since the input size is Ω( nk ). Experimental results show that the algorithms are fast in practice.

A consensus tree is a single phylogenetic tree that summarizes the branching structure in a given set of conflicting phylogenetic trees. Many different types of consensus trees have been proposed in the literature; three of the most well-known and widely used ones are the majority rule consensus tree, the loose consensus tree, and the greedy consensus tree. This paper presents new deterministic algorithms for constructing them that are faster than all the previously known ones. Given k phylogenetic trees with n leaves each and with identical leaf label sets, our algorithms run in O(nk log k) time (majority rule consensus tree), O(nk) time (loose consensus tree), and O(n2k) time (greedy consensus tree).