A new class of algorithms based on the triangle inequality has recently been proposed for use in contentbased image retrieval. These algorithms rely on comparing a set of key images to the database images, and storing the computed distances. Query images are later compared to the keys, and the triangle inequality is used to speedily compute lower bounds on the distance from the query to each of...

Pretropisms are candidates for the leading exponents of Puiseux series that represent positive dimensional solution sets of polynomial systems. We propose a new algorithm to both horizontally and vertically prune the tree of edges of a tuple of Newton polytopes. We provide experimental results with our preliminary implementation in Sage that demonstrates that our algorithm compares favorably to...

In saliency based pruning algorithms a pruning decision is made based on an ordering of the parameters. We will in this article focus on the fact that this ordering is invariant under certain transformations, and with that knowledge an equivalence class of algorithms is developed all yielding identical prunings. A sub-class is demonstrated to have a simple but sensible interpretation in terms o...

In this article we review standard null-move pruning and introduce our extended version of it, which we call verified null-move pruning. In verified null-move pruning, whenever the shallow null-move search indicates a fail-high, instead of cutting off the search from the current node, the search is continued with reduced depth. Our experiments with verified null-move pruning show that on averag...

This Supplementary Information further describes the methods used in DEEPer by providing additional details and proofs. Section A proves the validity of the indirect pruning algorithms, Algorithms 1 (proved in A.1) and 2 (in A.2), and derives their time complexity (A.3). Section B describes some details of implementation, relating to the application of perturbations (B.1) and the choice of prun...

Forward pruning, or selectively searching a subset of moves, is now commonly used in game-playing programs to reduce the number of nodes searched with manageable risk. Forward pruning techniques should consider how pruning errors in a game-tree search propagate to the root to minimize the risk of making errors. In this paper, we explore forward pruning using theoretical analyses and Monte Carlo...

Decision tree technology has proven to be a valuable way of capturing human decision making within a computer. It has long been a popular artificial intelligence(AI) technique. During the 1980s, it was one of the primary ways for creating an AI system. During the early part of the 1990s, it somewhat fell out of favor, as did the entire AI field in general. However, during the later 1990s, with ...

A large-scale pruning study was established in the winter of 1999 to2000 at seven different sites on Green Diamond Resource Company forestlands in Humboldt County. The objective of this study was to determine the effects of pruning on increment, epicormic sprouting, stem taper, heartwood formation, and bear damage on these young trees. Pruning treatments varied pruning severity and were usually...

Most speech recognition systems search through large finite state machines to find the most likely path, or hypothesis. Efficient search in these large spaces requires pruning of some hypotheses. Popular pruning techniques include probability pruning which keeps only hypotheses whose probability falls within a prescribed factor from the most likely one, and rank pruning which keeps only a presc...

The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorithms tend to have some or all of the following difficulties: 1) lack of theoretical support; 2) high computational complexity; 3) dependence on validation; 4) complicated implementation. The 2-norm pruning algorithm proposed here addresses all of the above difficulties. This paper demonstrates the...