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Take a multiplicative monoid of sequences in which the multiplication is given by Hadamard product. The set of linear combinations of interleaving monoid elements then yields a ring. For hypergeometric sequences, the resulting ring is a…

Symbolic Computation · Computer Science 2024-10-16 Bertrand Teguia Tabuguia

We present a simple combinatorial proof of Postnikov's hook length formula for binary trees.

Combinatorics · Mathematics 2007-05-23 William Y. C. Chen , Laura L. M. Yang

Classification of datasets into two or more distinct classes is an important machine learning task. Many methods are able to classify binary classification tasks with a very high accuracy on test data, but cannot provide any easily…

Machine Learning · Computer Science 2020-08-26 Yashesh Dhebar , Sparsh Gupta , Kalyanmoy Deb

We address the problem of learning binary decision trees that partition data for some downstream task. We propose to learn discrete parameters (i.e., for tree traversals and node pruning) and continuous parameters (i.e., for tree split…

Machine Learning · Computer Science 2021-06-15 Valentina Zantedeschi , Matt J. Kusner , Vlad Niculae

We construct generating trees with one, two, and three labels for some classes of permutations avoiding generalized patterns of length 3 and 4. These trees are built by adding at each level an entry to the right end of the permutation,…

Combinatorics · Mathematics 2007-08-01 Sergi Elizalde

The decision tree recursively partitions the input space into regions and derives axis-aligned decision boundaries from data. Despite its simplicity and interpretability, decision trees lack parameterized representation, which makes it…

Machine Learning · Computer Science 2024-11-19 Jinxiong Zhang

We derive tight bounds on the expected weights of several combinatorial optimization problems for random point sets of size $n$ distributed among the leaves of a balanced hierarchically separated tree. We consider {\it monochromatic} and…

Discrete Mathematics · Computer Science 2013-07-29 Béla Csaba , Thomas A. Plick , Ali Shokoufandeh

We present an axiomatic framework for analyzing the algorithmic properties of decision trees. This framework supports the classification of decision tree problems through structural and ancestral constraints within a rigorous mathematical…

Machine Learning · Computer Science 2025-10-24 Xi He , Max A. Little

Random forests have become an established tool for classification and regression, in particular in high-dimensional settings and in the presence of complex predictor-response relationships. For bounded outcome variables restricted to the…

Methodology · Statistics 2019-01-21 Leonie Weinhold , Matthias Schmid , Marvin N. Wright , Moritz Berger

A holonomic system of linear partial differential equations is, roughly speaking, a system whose solution space is finite dimensional. A distribution that is a solution of a holonomic system is called a holonomic distribution. We give…

Machine Learning · Computer Science 2024-11-01 Akihiro Sakoda , Nobuki Takayama

In this article we propose a heuristic algorithm to explore search space trees associated with instances of combinatorial optimization problems. The algorithm is based on Monte Carlo tree search, a popular algorithm in game playing that is…

Artificial Intelligence · Computer Science 2022-11-17 Jorik Jooken , Pieter Leyman , Tony Wauters , Patrick De Causmaecker

It has recently been shown that the NP-hard problem of calculating the minimum number of hybridization events that is needed to explain a set of rooted binary phylogenetic trees by means of a hybridization network is fixed-parameter…

Populations and Evolution · Quantitative Biology 2012-03-20 Leo van Iersel , Simone Linz

The amount of completely sequenced chloroplast genomes increases rapidly every day, leading to the possibility to build large-scale phylogenetic trees of plant species. Considering a subset of close plant species defined according to their…

Artificial Intelligence · Computer Science 2016-09-01 Bassam AlKindy , Bashar Al-Nuaimi , Christophe Guyeux , Jean-François Couchot , Michel Salomon , Reem Alsrraj , Laurent Philippe

The properties of randomly evolving special trees having defined and analyzed already in two earlier papers (arXiv:cond-mat/0205650 and arXiv:cond-mat/0211092) have been investigated in the case when the continuous time parameter converges…

Statistical Mechanics · Physics 2007-05-23 L. Pal

The Dollo model for reconstructing evolutionary trees from binary characters has been proposed as a generalization of the infinite sites model, also known as the Perfect Phylogeny. In particular, the Dollo model is considered more realistic…

Data Structures and Algorithms · Computer Science 2025-06-17 Paola Bonizzoni , Gianluca Della Vedova , Mauricio Soto Gomez , Gabriella Trucco

Random forests are ensemble methods which grow trees as base learners and combine their predictions by averaging. Random forests are known for their good practical performance, particularly in high dimensional set-tings. On the theoretical…

Statistics Theory · Mathematics 2015-09-18 Erwan Scornet

It is shown that the problem of computing the Strahler number of a binary tree given as a term is complete for the circuit complexity class uniform $\mathsf{NC}^1$. For several variants, where the binary tree is given by a pointer structure…

Computational Complexity · Computer Science 2025-12-23 Moses Ganardi , Markus Lohrey

Karloff? and Shirley recently proposed summary trees as a new way to visualize large rooted trees (Eurovis 2013) and gave algorithms for generating a maximum-entropy k-node summary tree of an input n-node rooted tree. However, the algorithm…

Data Structures and Algorithms · Computer Science 2014-04-24 Richard Cole , Howard Karloff

Many computational problems admit fast algorithms on special inputs, however, the required properties might be quite restrictive. E.g., many graph problems can be solved much faster on interval or cographs, or on graphs of small…

Data Structures and Algorithms · Computer Science 2022-09-30 Stefan Kratsch , Florian Nelles

We propose a slightly revised Miller-Hagberg (MH) algorithm that efficiently generates a random network from a given expected degree sequence. The revision was to replace the approximated edge probability between a pair of nodes with a…

Discrete Mathematics · Computer Science 2017-11-21 Hiroki Sayama
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