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For $f,g\in\omega\ho$ let $\mycfa_{f,g}$ be the minimal number of uniform $g$-splitting trees needed to cover the uniform $f$-splitting tree, i.e. for every branch $\nu$ of the $f$-tree, one of the $g$-trees contains $\nu$. $\myc_{f,g}$ is…

Logic · Mathematics 2011-01-25 Jakob Kellner , Saharon Shelah

We give the first {\sl reconstruction algorithm} for decision trees: given queries to a function $f$ that is $\mathrm{opt}$-close to a size-$s$ decision tree, our algorithm provides query access to a decision tree $T$ where: $\circ$ $T$ has…

Data Structures and Algorithms · Computer Science 2022-05-24 Guy Blanc , Jane Lange , Li-Yang Tan

We study the Excluded Grid Theorem, a fundamental structural result in graph theory, that was proved by Robertson and Seymour in their seminal work on graph minors. The theorem states that there is a function $f: \mathbb{Z}^+ \to…

Discrete Mathematics · Computer Science 2019-01-24 Julia Chuzhoy , Zihan Tan

In \cite{FKW} Katznelson and Weiss establish that all sufficiently large distances can always be attained between pairs of points from any given measurable subset of $\mathbb{R}^2$ of positive upper (Banach) density. A second proof of this…

Number Theory · Mathematics 2019-02-07 Neil Lyall , Akos Magyar

In this paper we examine the problem of inference in Bayesian Networks with discrete random variables that have very large or even unbounded domains. For example, in a domain where we are trying to identify a person, we may have variables…

Artificial Intelligence · Computer Science 2012-12-12 Rita Sharma , David L Poole

In this paper we derive tight bounds on the expected value of products of {\em low influence} functions defined on correlated probability spaces. The proofs are based on extending Fourier theory to an arbitrary number of correlated…

Probability · Mathematics 2009-06-01 Elchanan Mossel

We report on work towards flexible algorithms for solving decision problems represented as influence diagrams. An algorithm is given to construct a tree structure for each decision node in an influence diagram. Each tree represents a…

Artificial Intelligence · Computer Science 2013-02-18 Michael C. Horsch , David L. Poole

Decision trees have long been recognized as models of choice in sensitive applications where interpretability is of paramount importance. In this paper, we examine the computational ability of Boolean decision trees in deriving, minimizing,…

Artificial Intelligence · Computer Science 2021-09-07 Gilles Audemard , Steve Bellart , Louenas Bounia , Frédéric Koriche , Jean-Marie Lagniez , Pierre Marquis

Given a continuous real-valued function on [0, 1], and a closed subset E \subset [0, 1] we denote by f E the restriction of f to E, that is, the function defined only on E that takes the same values as f at every point of E >. The…

Classical Analysis and ODEs · Mathematics 2007-11-29 Jean-Pierre Kahane , Yitzhak Katznelson

We prove a Lusin approximation of functions of bounded variation. If $f$ is a function of bounded variation on an open set $\Omega\subset X$, where $X=(X,d,\mu)$ is a given complete doubling metric measure space supporting a $1$-Poincar\'e…

Functional Analysis · Mathematics 2025-01-14 Panu Lahti , Khanh Nguyen

We study the probability of Boolean functions with small max influence to become constant under random restrictions. Let $f$ be a Boolean function such that the variance of $f$ is $\Omega(1)$ and all its individual influences are bounded by…

Computational Complexity · Computer Science 2022-08-19 Ronen Eldan , Avi Wigderson , Pei Wu

In this note we compare two measures of the complexity of a class $\mathcal F$ of Boolean functions studied in (unconditional) pseudorandomness: $\mathcal F$'s ability to distinguish between biased and uniform coins (the coin problem), and…

Computational Complexity · Computer Science 2020-09-01 Rohit Agrawal

We give strengthened provable guarantees on the performance of widely employed and empirically successful {\sl top-down decision tree learning heuristics}. While prior works have focused on the realizable setting, we consider the more…

Data Structures and Algorithms · Computer Science 2020-06-02 Guy Blanc , Jane Lange , Li-Yang Tan

We study a constructive algorithm that approximates Gateaux derivatives for statistical functionals by finite differencing, with a focus on functionals that arise in causal inference. We study the case where probability distributions are…

Methodology · Statistics 2026-03-16 Michael I. Jordan , Yixin Wang , Angela Zhou

The depth-weighted tree DWT($f$) with weight function $f:\{0,1,2,\ldots\}\to (0,\infty)$ is a dynamic random tree grown from a root $r$ where vertices arrive consecutively and every new vertex attaches to a parent $u$ with probability…

Probability · Mathematics 2026-02-18 Lyuben Lichev , Amitai Linker , Bas Lodewijks , Dieter Mitsche

Treedepth, a more restrictive graph width parameter than treewidth and pathwidth, plays a major role in the theory of sparse graph classes. We show that there exists a constant $C$ such that for every positive integers $a,b$ and a graph…

Discrete Mathematics · Computer Science 2019-09-19 Wojciech Czerwiński , Wojciech Nadara , Marcin Pilipczuk

This paper concerns algorithms that give correct answers with (asymptotic) density $1$. A dense description of a function $g : \omega \to \omega$ is a partial function $f$ on $\omega$ such that $\left\{n : f(n) = g(n)\right\}$ has density…

Logic · Mathematics 2018-11-20 Eric P. Astor , Denis R. Hirschfeldt , Carl G. Jockusch

Let $n\geq 1$, $K>0$, and let $X=(X_1,X_2,\dots,X_n)$ be a random vector in $\mathbb{R}^n$ with independent $K$--subgaussian components. We show that for every $1$--Lipschitz convex function $f$ in $\mathbb{R}^n$ (the Lipschitzness with…

Probability · Mathematics 2023-05-02 Han Huang , Konstantin Tikhomirov

Consider a Boolean function f on the n-dimensional hypercube, and a set of variables (indexed by) $S \subset \{1,2,\ldots,n\}.$ The coalition influence of the variables S on a function f is the probability that after a random assignment of…

Combinatorics · Mathematics 2026-01-19 Tomasz Przybyłowski

We consider functions $f$ of two real variables, given as trigonometric functions over a finite set $F$ of frequencies. This set is assumed to be closed under rotations in the frequency plane of angle $\frac{2k\pi}{M}$ for some integer $M$.…

Numerical Analysis · Mathematics 2016-12-02 Jean-Paul Gauthier , Dario Prandi