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Self‐adjusting trees in practice for large text collections

Hugh E. Williams, Justin Zobel, Steffen Heinz
2001 Software, Practice & Experience  
Splay and randomised search trees are self-balancing binary tree structures with little or no space overhead compared to a standard binary search tree.  ...  Surprisingly, unmodified splaying and randomised search trees are on average around 25% slower than using a standard binary tree.  ...  RANDOMISED SEARCH TREES Randomised search trees [18] are another variation of binary search trees that employ rotation heuristics to achieve expected bounds comparable to the amortised bounds of the  ... 
doi:10.1002/spe.394 fatcat:v25hj5pjjrbzfmi2ajmn4w723m

Genetic Programming Bloat without Semantics [chapter]

W. B. Langdon, W. Banzhaf
2000 Lecture Notes in Computer Science  
To investigate the fundamental causes of bloat, six arti cial random binary tree search spaces are presented. Fitness is given by program syntax (the genetic programming genotype).  ...  To investigate the di erences between these a series of arti cial random binary tree search spaces are presented.  ...  Random Binary Tree Search Spaces The programs are composed of four functions, opcodes 0 : : : 3, and six terminals (leafs), opcodes 4 : : : 9 (cf. Fig. 1 ).  ... 
doi:10.1007/3-540-45356-3_20 fatcat:nkqcgblnmvh57kyxjsphmnwkku

Verified Analysis of Random Binary Tree Structures

Manuel Eberl, Max W. Haslbeck, Tobias Nipkow
2020 Journal of automated reasoning  
random Binary Search Tree, the randomised binary search trees described by Martínez and Roura, and the expected shape of a randomised treap.  ...  In particular, we consider the expected number of comparisons in randomised quicksort, the relationship between randomised quicksort and average-case deterministic quicksort, the expected shape of an unbalanced  ...  We thank Johannes Hölzl and Andreas Lochbihler for helpful discussions, Johannes Hölzl for his help with the construction of the tree space, and Bohua Zhan and Maximilian P. L.  ... 
doi:10.1007/s10817-020-09545-0 fatcat:qoyl4mininf2fhowpcwtbwhj4q

Random Binary Trees for Approximate Nearest Neighbour Search in Binary Space [article]

Michal Komorowski, Tomasz Trzcinski
2019 arXiv   pre-print
In this paper, we focus on ANN for high-dimensional binary vectors and we propose a simple yet powerful search method that uses Random Binary Search Trees (RBST).  ...  Approximate nearest neighbour (ANN) search is one of the most important problems in computer science fields such as data mining or computer vision.  ...  Our proposed RBST may also look similar to Randomised Binary Search Trees [14] . However, there are few differences.  ... 
arXiv:1708.02976v2 fatcat:z2p56c5tr5d6zbatui6ipyu3b4

On Learning a Hidden Directed Graph with Path Queries [article]

Mano Vikash Janardhanan, Lev Reyzin
2021 arXiv   pre-print
We then study the case of bounded degree directed trees and give new algorithms for learning "almost-trees" -- directed trees to which extra edges have been added.  ...  Every time the randomised binary search picks a vertex in i ∈ P ′ \ P , we will end up deleting all the children of i from the potential vertices for the next iteration of the randomised binary search  ...  Its presence will be felt only in the randomised binary search (in Algorithm 4) as there may be two paths from the root to vertex i.  ... 
arXiv:2002.11541v2 fatcat:e7zilyzdaval3hg4y4rmsoxcky

On XTR and Side-Channel Analysis [chapter]

Daniel Page, Martijn Stam
2004 Lecture Notes in Computer Science  
Binary Exponentiation Exponent Randomisation.  ...  our search.  ...  This is especially handy for the binary exponentiation algorithm. Computation of c n+m boils down to computing One cn+m call Operation Two c2n calls  ... 
doi:10.1007/978-3-540-30564-4_4 fatcat:vrowulchzndebarhfokl7f37le

Real-Time SLAM Relocalisation

Brian Williams, Georg Klein, Ian Reid
2007 2007 IEEE 11th International Conference on Computer Vision  
As may be expected, simplyfing the posterior to a binary score reduces classification performance for equal tree depths; however the binary score outperforms the full posterior when using the same memory  ...  Randomised Lists for SLAM recovery If the tests are random, it is not necessary for the tests at any one level of a tree to be different.  ... 
doi:10.1109/iccv.2007.4409115 dblp:conf/iccv/WilliamsKR07 fatcat:ynvrnaaqcffxziddpphwex6yc4

Feature-subspace aggregating: ensembles for stable and unstable learners

Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb
2010 Machine Learning  
When SVM is the preferred base learner, we show that Feating SVM performs better than Boosting decision trees and Random Forests.  ...  We further demonstrate that Feating also substantially reduces the error of another stable learner, k-nearest neighbour, and an unstable learner, decision tree.  ...  The highest h values are found in just two examinations in the binary search for connect-4 and usps.  ... 
doi:10.1007/s10994-010-5224-5 fatcat:fadxjnizfvgsvggnefbztxqz4a

Perioperative adjuvant corticosteroids for post-operative analgesia in elective knee surgery – A systematic review

Hasan Raza Mohammad, Marialena Trivella, Thomas W. Hamilton, Louise Strickland, David Murray, Hemant Pandit
2017 Systematic Reviews  
Methods: The databases MEDLINE, EMBASE and CENTRAL (Cochrane library) will be searched from their inception to present using broad search criteria for eligible randomised/quasi-randomised controlled trials  ...  Acknowledgements The authors would like to thank Eli Harris, librarian from the Oxford Bodleian libraries, for assisting in quality assuring our employed search strategy for this review.  ...  We will measure this as binary data.  ... 
doi:10.1186/s13643-017-0485-8 pmid:28449696 pmcid:PMC5406982 fatcat:h7elnb2u3bcejc7mrgrmqkpwl4

Evaluation of Hidden Surface Removal Methods Using Open GL

Lubna Saeed, Fakhrulddin Ali
2021 Al-Rafidain Engineering Journal  
However, the most popular methods used widely nowadays are depth or Z-Buffer (ZB) and Binary Space Partition Tree (BSPT).  ...  Modelling graphical database in a binary tree make the dealing with parts of the database feasible. This is so important for clipping a part or more of the database when outside the viewing zone.  ...  random Binary Search Tree, the randomised binary search trees described by Martínez and Roura, and the expected shape of a randomised treap.  ... 
doi:10.33899/rengj.2021.129472.1081 fatcat:3ir4o2obazcsflgue4zpkqdclu

Dynamic Z-Fast Tries [chapter]

Djamal Belazzougui, Paolo Boldi, Sebastiano Vigna
2010 Lecture Notes in Computer Science  
We describe a dynamic version of the z-fast trie, a new data structure inspired by the research started by the van Emde Boas trees [12] and followed by the development of y-fast tries [13].  ...  The structure described in this paper is inspired by the idea of fat binary search introduced therein, but has little else in common.  ...  Additionaly, the z-fast trie uses a dictionary, inspired by the static case, to locate quickly the exit node of a string using a variant of the fat binary search.  ... 
doi:10.1007/978-3-642-16321-0_15 fatcat:sgpb5jkrj5cbbngivj2xntijb4

Combining online and offline knowledge in UCT

Sylvain Gelly, David Silver
2007 Proceedings of the 24th international conference on Machine learning - ICML '07  
Third, the offline value function is used as prior knowledge in the UCT search tree. We evaluate these algorithms in 9 × 9 Go against GnuGo 3.7.10.  ...  The UCT algorithm learns a value function online using sample-based search. The T D(λ) algorithm can learn a value function offline for the on-policy distribution.  ...  In the beginning of each episode it selects actions according to knowledge contained within the search tree. But once it leaves the scope of its search tree it has no knowledge and behaves randomly.  ... 
doi:10.1145/1273496.1273531 dblp:conf/icml/GellyS07 fatcat:ruxwj2nu6zes5hi5rosgqwk55a

Optimised KD-trees for fast image descriptor matching

Chanop Silpa-Anan, Richard Hartley
2008 2008 IEEE Conference on Computer Vision and Pattern Recognition  
KD-tree [4], which is a form of balanced binary search tree.  ...  Each of the two halves of the data is then recursively split in the same way to create a fully balanced binary tree.  ...  Previous work The KD-tree was introduced in [5] as a generalisation of a binary tree to high dimensions.  ... 
doi:10.1109/cvpr.2008.4587638 dblp:conf/cvpr/Silpa-AnanH08 fatcat:fjfo24niafavjjmlhsmzmdifmi

Streaming dictionary matching with mismatches [article]

Paweł Gawrychowski, Tatiana Starikovskaya
2021 arXiv   pre-print
The algorithm is randomised and outputs correct answers with high probability.  ...  First, we store a binary search tree on the set of the starting positions of all blocks containing a mismatch.  ...  We can then re-build the binary search tree inÕ(k) time and compute the sketches for the O(k) mismatch-containing blocks inÕ(k 2 d) time.  ... 
arXiv:1809.02517v3 fatcat:wa53lyafcvfbjgm5lkvbpbxmdi

Digital Access to Comparison-Based Tree Data Structures and Algorithms

Salvador Roura
2001 Journal of Algorithms  
This paper presents a simple method to build tree data structures which achieve just O(log N) visited nodes and O(D) compared digits (bits or bytes) per search or update, where N is the number of keys  ...  Digital searches in binary search trees In this section we will see how to perform searches in binary search trees (balanced or not) comparing each bit at most once.  ...  Figure 7 : 7 Classic and digital searches in binary search trees.  ... 
doi:10.1006/jagm.2001.1160 fatcat:jlfxe53uibbkfkiv4obsk5fgja
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