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Algorithms for learning decision trees often include heuristic local-search operations such as (1) adjusting the threshold of a cut or (2) also exchanging the feature of that cut. We study minimizing the number of classification errors by…

Machine Learning · Computer Science 2025-10-15 Juha Harviainen , Frank Sommer , Manuel Sorge

We investigate linear and additive codes in partially ordered Hamming-like spaces that satisfy the extension property, meaning that automorphisms of ideals extend to automorphisms of the poset. The codes are naturally described in terms of…

Information Theory · Computer Science 2013-12-18 Alexander Barg , Luciano V. Felix , Marcelo Firer , Marcos V. P. Spreafico

Additive regression provides an extension of linear regression by modeling the signal of a response as a sum of functions of covariates of relatively low complexity. We study penalized estimation in high-dimensional nonparametric additive…

Statistics Theory · Mathematics 2017-04-25 Zhiqiang Tan , Cun-Hui Zhang

Asymptotic analysis on some statistical properties of the random binary-tree model is developed. We quantify a hierarchical structure of branching patterns based on the Horton-Strahler analysis. We introduce a transformation of a binary…

Mathematical Physics · Physics 2013-06-03 Ken Yamamoto , Yoshihiro Yamazaki

The classes of tree permutations and forest permutations were defined by Acan and Hitczenko (2016). We study random permutations of a given length from these classes, and in particular the number of occurrences of a fixed pattern in one of…

Combinatorics · Mathematics 2022-03-10 Svante Janson

We provide finite-sample distribution approximations, that are uniform in the parameter, for inference in linear mixed models. Focus is on variances and covariances of random effects in cases where existing theory fails because their…

Statistics Theory · Mathematics 2025-07-29 Karl Oskar Ekvall , Matteo Bottai

Adaptive binary search trees are a fundamental data structure for organizing hierarchical information. Their ability to dynamically adjust to access patterns makes them particularly valuable for building responsive and efficient networked…

Data Structures and Algorithms · Computer Science 2025-07-29 Maryam Shiran

We prove limit theorems for sums of functions of subtrees of binary search trees and random recursive trees. In particular, we give simple new proofs of the fact that the number of fringe trees of size $ k=k_n $ in the binary search tree…

Probability · Mathematics 2014-06-27 Cecilia Holmgren , Svante Janson

Agentic large language model (LLM) training often involves multi-turn interaction trajectories that branch into multiple execution paths due to concurrent tool use, think-mode, sub-agent, context management and other runtime designs. As a…

We study the space requirement of $m$-ary search trees under the random permutation model when $m \geq 27$ is fixed. Chauvin and Pouyanne have shown recently that $X_n$, the space requirement of an $m$-ary search tree on $n$ keys, equals…

Probability · Mathematics 2007-05-23 James Allen Fill , Nevin Kapur

The computational complexity of time-dependent perturbation theory is well-known to be largely combinatorial whatever the chosen expansion method and family of parameters (combinatorial sequences, Goldstone and other Feynman-type…

Strongly Correlated Electrons · Physics 2010-07-26 Christian Brouder , Ângela Mestre , Frédéric Patras

A weighted recursive tree is an evolving tree in which vertices are assigned random vertex-weights and new vertices connect to a predecessor with a probability proportional to its weight. Here, we study the maximum degree and near-maximum…

Probability · Mathematics 2023-01-31 Laura Eslava , Bas Lodewijks , Marcel Ortgiese

Vast literature on experimental design extends from Fisher and Snedecor to the modern day. When data lies beyond the assumption of univariate normality, nonparametric methods including rank based statistics and permutation tests are…

Statistics Theory · Mathematics 2022-05-30 Adam B Kashlak , Sergii Myroshnychenko , Susanna Spektor

We study the statistics of height and balanced height in the binary search tree problem in computer science. The search tree problem is first mapped to a fragmentation problem which is then further mapped to a modified directed polymer…

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , P. L. Krapivsky

The dynamics of a rain forest is extremely complex involving births, deaths and growth of trees with complex interactions between trees, animals, climate, and environment. We consider the patterns of recruits (new trees) and dead trees…

Methodology · Statistics 2024-09-19 Abdollah Jalilian , Francisco Cuevas-Pacheco , Ganggang Xu , Rasmus Waagepetersen

This paper is part of the general project of proof mining, developed by Kohlenbach. By "proof mining" we mean the logical analysis of mathematical proofs with the aim of extracting new numerically relevant information hidden in the proofs.…

Logic · Mathematics 2008-01-14 Laurentiu Leustean

In arithmetic statistics and analytic number theory, the asymptotic growth rate of counting functions giving the number of objects with order below $X$ is studied as $X\to \infty$. We define general counting functions which count…

Number Theory · Mathematics 2023-03-22 Brandon Alberts

Hash codes are a very efficient data representation needed to be able to cope with the ever growing amounts of data. We introduce a random forest semantic hashing scheme with information-theoretic code aggregation, showing for the first…

Computer Vision and Pattern Recognition · Computer Science 2015-04-20 Qiang Qiu , Guillermo Sapiro , Alex Bronstein

Recent years have seen tremendous growth in the amount of verified software. Proofs for complex properties can now be achieved using higher-order theories and calculi. Complex properties lead to an ever-growing number of definitions and…

Programming Languages · Computer Science 2021-11-29 Eytan Singher , Shachar Itzhaky

Decision trees are important both as interpretable models amenable to high-stakes decision-making, and as building blocks of ensemble methods such as random forests and gradient boosting. Their statistical properties, however, are not well…

Machine Learning · Statistics 2021-10-20 Yan Shuo Tan , Abhineet Agarwal , Bin Yu
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