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The slow-coloring game is played by Lister and Painter on a graph $G$. On each round, Lister marks a nonempty subset $M$ of the remaining vertices, scoring $|M|$ points. Painter then gives a color to a subset of $M$ that is independent in…

Combinatorics · Mathematics 2017-10-04 Gregory J. Puleo , Douglas B. West

We introduce a variant of the well-studied sum choice number of graphs, which we call the interactive sum choice number. In this variant, we request colours to be added to the vertices' colour-lists one at a time, and so we are able to make…

Discrete Mathematics · Computer Science 2021-01-07 Marthe Bonamy , Kitty Meeks

Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5--32] that combines several randomized decision trees and aggregates their predictions by averaging. Despite its wide usage and outstanding practical…

Statistics Theory · Mathematics 2015-08-11 Erwan Scornet , Gérard Biau , Jean-Philippe Vert

Coloring is a notoriously hard problem, and even more so in the online setting, where each arriving vertex has to be colored immediately and irrevocably. Already on trees, which are trivially two-colorable, it is impossible to achieve…

Data Structures and Algorithms · Computer Science 2024-05-29 Fabian Frei , Matthias Gehnen , Dennis Komm , Rastislav Královič , Richard Královič , Peter Rossmanith , Moritz Stocker

While the game chromatic number of a forest is known to be at most 4, no simple criteria are known for determining the game chromatic number of a forest. We first state necessary and sufficient conditions for forests with game chromatic…

Combinatorics · Mathematics 2014-10-21 Charles Dunn , Victor Larsen , Kira Lindke , Troy Retter , Dustin Toci

Additive feature explanations using Shapley values have become popular for providing transparency into the relative importance of each feature to an individual prediction of a machine learning model. While Shapley values provide a unique…

Machine Learning · Computer Science 2021-12-21 Thomas W. Campbell , Heinrich Roder , Robert W. Georgantas , Joanna Roder

Random Forests are one of the most popular classifiers in machine learning. The larger they are, the more precise is the outcome of their predictions. However, this comes at a cost: their running time for classification grows linearly with…

Machine Learning · Computer Science 2019-12-24 Frederik Gossen , Bernhard Steffen

Constrained forest problems form a class of graph problems where specific connectivity requirements for certain cuts within the graph must be satisfied by selecting the minimum-cost set of edges. The prize-collecting version of these…

Data Structures and Algorithms · Computer Science 2025-04-23 Ali Ahmadi , Iman Gholami , MohammadTaghi Hajiaghayi , Peyman Jabbarzade , Mohammad Mahdavi

The most fundamental problem in statistical causality is determining causal relationships from limited data. Probability trees, which combine prior causal structures with Bayesian updates, have been suggested as a possible solution. In this…

Machine Learning · Computer Science 2022-05-19 Tue Herlau

Let G=(V,E) be a graph and let f be a function that assigns list sizes to the vertices of G. It is said that G is f-choosable if for every assignment of lists of colors to the vertices of G for which the list sizes agree with f, there…

Combinatorics · Mathematics 2013-05-10 Michelle Lastrina , Michael Young

Random forests are a scheme proposed by Leo Breiman in the 2000's for building a predictor ensemble with a set of decision trees that grow in randomly selected subspaces of data. Despite growing interest and practical use, there has been…

Machine Learning · Statistics 2012-03-28 Gérard Biau

Every weighted tree corresponds naturally to a cooperative game that we call a "tree game"; it assigns to each subset of leaves the sum of the weights of the minimal subtree spanned by those leaves. In the context of phylogenetic trees, the…

Quantitative Methods · Quantitative Biology 2009-09-02 Claus-Jochen Haake , Akemi Kashiwada , Francis Edward Su

Tree ensemble methods such as random forests [Breiman, 2001] are very popular to handle high-dimensional tabular data sets, notably because of their good predictive accuracy. However, when machine learning is used for decision-making…

Statistics Theory · Mathematics 2021-12-28 Erwan Scornet

Board games have shown promise as educational tools, but their use in engaging learners with the complex, long-term trade-offs of forest management remains strikingly underdeveloped. Addressing this gap, we investigate how forest growth…

Human-Computer Interaction · Computer Science 2026-04-07 Arka Majhi , Daniel Fernández Galeote , Timo Nummenmaa , Juho Hamari , Aaron Petty , Jari Vauhkonen , Heli Peltola

Variable selection for high-dimensional linear models has received a lot of attention lately, mostly in the context of l1-regularization. Part of the attraction is the variable selection effect: parsimonious models are obtained, which are…

Machine Learning · Statistics 2009-06-22 Nicolai Meinshausen

In this work, we investigate various combinatorial properties of Borel ideals on countable sets. We extend a theorem presented in M. Hru\v{s}\'{a}k, D. Meza-Alc\'antara, E. Th\"ummel, and C. Uzc\'ategui, \emph{Ramsey Type Properties of…

Logic · Mathematics 2025-02-07 José de Jesús Pelayo Gómez

Consider the following game. We are given a tree $T$ and two players (say) Alice and Bob who alternately colour an edge of a tree (using one of $k$ colours). If all edges of the tree get coloured, then Alice wins else Bob wins. Game…

Data Structures and Algorithms · Computer Science 2020-02-11 Akshay Singh , Sanjeev Saxena

The slow coloring game was introduced by Mahoney, Puleo, and West and it is played by two players, Lister and Painter, on a graph \(G\). In round \(i\), Lister marks a nonempty subset \(M\) of \(V(G)\). By doing this he scores \(|M|\)…

Combinatorics · Mathematics 2023-04-05 Joan Morris , Gregory Puleo

It is becoming increasingly important for machine learning methods to make predictions that are interpretable as well as accurate. In many practical applications, it is of interest which features and feature interactions are relevant to the…

Machine Learning · Statistics 2016-02-09 Viktoriya Krakovna , Jiong Du , Jun S. Liu

This article introduces a flexible and adaptive nonparametric method for estimating the association between multiple covariates and power spectra of multiple time series. The proposed approach uses a Bayesian sum of trees model to capture…

Methodology · Statistics 2021-10-01 Yakun Wang , Zeda Li , Scott A. Bruce
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