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We introduce the zip tree, a form of randomized binary search tree that integrates previous ideas into one practical, performant, and pleasant-to-implement package. A zip tree is a binary search tree in which each node has a numeric rank…

Data Structures and Algorithms · Computer Science 2022-02-23 Robert E. Tarjan , Caleb C. Levy , Stephen Timmel

Treemaps have been widely applied to the visualization of hierarchical data. A treemap takes a weighted tree and visualizes its leaves in a nested planar geometric shape, with sub-regions partitioned such that each sub-region has an area…

Graphics · Computer Science 2023-09-01 Mehdi Behroozi , Reyhaneh Mohammadi , Cody Dunne

The Kolmogorov-Arnold representation is a proven adequate replacement of a continuous multivariate function by an hierarchical structure of multiple functions of one variable. The proven existence of such representation inspired many…

Optimization and Control · Mathematics 2020-06-23 Andrew Polar , Michael Poluektov

Phylogenetic networks are leaf-labelled directed acyclic graphs that are used to describe non-treelike evolutionary histories and are thus a generalization of phylogenetic trees. The hybridization number of a phylogenetic network is the sum…

Data Structures and Algorithms · Computer Science 2016-06-01 Leo van Iersel , Steven Kelk , Nela Lekić , Chris Whidden , Norbert Zeh

The Calkin-Wilf tree is an infinite binary tree whose vertices are the positive rational numbers. Each number occurs in the tree exactly once and in the form $a/b$, where are $a$ and $b$ are relatively prime positive integers. In this…

Number Theory · Mathematics 2020-04-17 Melvyn B. Nathanson

The Horton-Strahler (HS) index $r=\max{(i,j)}+\delta_{i,j}$ has been shown to be relevant to a number of physical (such at diffusion limited aggregation) geological (river networks), biological (pulmonary arteries, blood vessels, various…

Statistical Mechanics · Physics 2009-11-07 Z. Toroczkai

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions…

Machine Learning · Computer Science 2010-06-29 Shankar Vembu

For enumerative problems, i.e. computable functions f from N to Z, we define the notion of an effective (or closed) formula. It is an algorithm computing f(n) in the number of steps that is polynomial in the combined size of the input n and…

Combinatorics · Mathematics 2018-09-11 Martin Klazar

The forest-of-octrees approach to parallel adaptive mesh refinement and coarsening (AMR) has recently been demonstrated in the context of a number of large-scale PDE-based applications. Although linear octrees, which store only leaf…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-05 Tobin Isaac , Carsten Burstedde , Lucas C. Wilcox , Omar Ghattas

We present an algorithm for effectively generating binary sequences which would be rated by people as highly likely to have been generated by a random process, such as flipping a fair coin.

Human-Computer Interaction · Computer Science 2008-10-05 Yasmine B. Sanderson

Labeled infinite trees provide combinatorial interpretations for many integer sequences generated by nested recurrence relations. Typically, such sequences are monotone increasing. Several of these sequences also have straightforward…

Combinatorics · Mathematics 2022-11-07 Nathan Fox

Sturmian words are infinite binary words with many equivalent definitions: They have a minimal factor complexity among all aperiodic sequences; they are balanced sequences (the labels 0 and 1 are as evenly distributed as possible) and they…

Discrete Mathematics · Computer Science 2008-09-12 Nicolas Gast , Bruno Gaujal

A central limit theorem for binary tree is numerically examined. Two types of central limit theorem for higher-order branches are formulated. A topological structure of a binary tree is expressed by a binary sequence, and the…

Data Analysis, Statistics and Probability · Physics 2013-04-10 Ken Yamamoto , Yoshihiro Yamazaki

In this article we present a machine learning model to obtain fast and accurate estimates of the molecular Hessian matrix. In this model, based on a random forest, the second derivatives of the energy with respect to redundant internal…

Chemical Physics · Physics 2024-01-10 Giorgio Domenichini , Christoph Dellago

For an arbitrary tree we investigate the problems of constructing a maximum matching which minimizes or maximizes the cardinality of a maximum matching of the graph obtained from original one by its removal and present corresponding…

Discrete Mathematics · Computer Science 2007-07-17 R. R. Kamalian , V. V. Mkrtchyan

Model trees provide an appealing way to perform interpretable machine learning for both classification and regression problems. In contrast to ``classic'' decision trees with constant values in their leaves, model trees can use linear…

Machine Learning · Computer Science 2026-03-11 Sabino Francesco Roselli , Eibe Frank

Recent work has shown that the input-output behavior of some machine learning systems can be captured symbolically using Boolean expressions or tractable Boolean circuits, which facilitates reasoning about the behavior of these systems.…

Artificial Intelligence · Computer Science 2020-07-06 Arthur Choi , Andy Shih , Anchal Goyanka , Adnan Darwiche

Many interesting computational problems can be reformulated in terms of decision trees. A natural classical algorithm is to then run a random walk on the tree, starting at the root, to see if the tree contains a node n levels from the root.…

Quantum Physics · Physics 2009-10-30 Edward Farhi , Sam Gutmann

Efficient index structures for fast approximate nearest neighbor queries are required in many applications such as recommendation systems. In high-dimensional spaces, many conventional methods suffer from excessive usage of memory and slow…

Supervised hashing aims to map the original features to compact binary codes that are able to preserve label based similarity in the Hamming space. Non-linear hash functions have demonstrated the advantage over linear ones due to their…

Computer Vision and Pattern Recognition · Computer Science 2016-11-17 Guosheng Lin , Chunhua Shen , Qinfeng Shi , Anton van den Hengel , David Suter