This paper presents an experimental comparison of two Inductive Logic Programming algorithms, Progol and Tilde , with C4.5, a propo-sitional learning algorithm, on a propositional dataset of road traac accidents. Rebalancing methods are described for handling the skewed distribution of positive and negative examples in this dataset, and the relative cost of errors of commission and omission in ...

We address the concurrent rebalancing of almost balanced binary search trees (AVL trees). Such a rebalancing may for instance be necessary after successive insertions and deletions of keys. We show that this problem can be studied through the self-reorganization of distributed systems of nodes controlled by local evolution rules in the line of the approach of Dijkstra and Scholten. This yields ...

In the research of Facial Expression Recognition (FER), inter-class facial expression data is not evenly distributed, features extracted by networks are insufficient, and FER accuracy speed relatively low for practical applications. Therefore, a lightweight efficient method based on class-rebalancing fusion cumulative learning proposed in our research. A dual-branch network (Regular feature Reb...

A major driver of cost growth in health care is the rapid increase in the utilisation of existing technology and not simply the adoption of new technology. Health economists and their health technology assessment colleagues have become obsessed by technology adoption questions and have largely ignored 'technology management' questions. Technology management would include the life-cycle assessme...

In this thesis, various methods for maintaining balanced search trees in main memory are considered. The work concentrates on algorithms applying relaxed balancing in which updates and rebalancing are uncoupled from each other. A new relaxed balanced tree, the rank-valued tree, which is a relaxed version of symmetric binary B-trees, also known as red-black trees, is introduced and analyzed. Ran...