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We present a randomized algorithm that computes a constant approximation of a graph's arboricity, using $\tilde{O}(n/\lambda)$ queries to adjacency lists and in the same time bound. Here, $n$ and $\lambda$ denote the number of nodes and the…

Data Structures and Algorithms · Computer Science 2025-12-23 Jiangqi Dai , Mohsen Ghaffari , Julian Portmann

In this paper we consider the variational approach to cactus trees (Husimi trees) and the more common recursive approach, that are in principle equivalent for finite systems. We discuss in detail the conditions under which the two methods…

Statistical Mechanics · Physics 2007-05-23 Marco Pretti

Recent work has discussed the limitations of counterfactual explanations to recommend actions for algorithmic recourse, and argued for the need of taking causal relationships between features into consideration. Unfortunately, in practice,…

Machine Learning · Computer Science 2020-10-26 Amir-Hossein Karimi , Julius von Kügelgen , Bernhard Schölkopf , Isabel Valera

We give an algorithm for finding the arboricity of a weighted, undirected graph, defined as the minimum number of spanning forests that cover all edges of the graph, in $\sqrt{n} m^{1+o(1)}$ time. This improves on the previous best bound of…

Data Structures and Algorithms · Computer Science 2025-07-22 Ruoxu Cen , Henry Fleischmann , George Z. Li , Jason Li , Debmalya Panigrahi

Uniform attachment with freezing is an extension of the classical model of random recursive trees, in which trees are recursively built by attaching new vertices to old ones. In the model of uniform attachment with freezing, vertices are…

Probability · Mathematics 2026-05-05 Anna Brandenberger , Simon Briend , Hannah Cairns , Robin Khanfir , Igor Kortchemski

Assume we are given a set of items from a general metric space, but we neither have access to the representation of the data nor to the distances between data points. Instead, suppose that we can actively choose a triplet of items (A,B,C)…

Machine Learning · Statistics 2018-06-19 Siavash Haghiri , Damien Garreau , Ulrike von Luxburg

Random forests are a very effective and commonly used statistical method, but their full theoretical analysis is still an open problem. As a first step, simplified models such as purely random forests have been introduced, in order to shed…

Statistics Theory · Mathematics 2014-07-16 Sylvain Arlot , Robin Genuer

We revisit the problem max-min degree arborescence, which was introduced by Bateni et al. [STOC'09] as a central special case of the general Santa Claus problem, which constitutes a notorious open question in approximation algorithms. In…

Data Structures and Algorithms · Computer Science 2022-11-28 Étienne Bamas , Lars Rohwedder

The Maximum Agreement Forest (Maf) problem is a well-studied problem in evolutionary biology, which asks for a largest common subforest of a given collection of phylogenetic trees with identical leaf label-set. However, the previous work…

Data Structures and Algorithms · Computer Science 2014-11-04 Feng Shi , Jianer Chen , Qilong Feng , Xiaojun Ding , Jianxin Wang

Online Convex Optimization plays a key role in large scale machine learning. Early approaches to this problem were conservative, in which the main focus was protection against the worst case scenario. But recently several algorithms have…

Machine Learning · Computer Science 2016-09-09 Parameswaran Kamalaruban

We propose an algorithm named best-scored random forest for binary classification problems. The terminology "best-scored" means to select the one with the best empirical performance out of a certain number of purely random tree candidates…

Machine Learning · Statistics 2019-05-28 Hanyuan Hang , Xiaoyu Liu , Ingo Steinwart

We analyse a maximum-likelihood approach for combining phylogenetic trees into a larger `supertree'. This is based on a simple exponential model of phylogenetic error, which ensures that ML supertrees have a simple combinatorial description…

Populations and Evolution · Quantitative Biology 2007-08-17 Mike Steel , Allen Rodrigo

Algorithmic recourse aims to provide actionable recommendations to individuals to obtain a more favourable outcome from an automated decision-making system. As it involves reasoning about interventions performed in the physical world,…

Machine Learning · Statistics 2021-06-23 Julius von Kügelgen , Nikita Agarwal , Jakob Zeitler , Afsaneh Mastouri , Bernhard Schölkopf

In the random-order online set cover problem, the instance with $m$ sets and $n$ elements is chosen in a worst-case fashion, but then the elements arrive in a uniformly random order. Can this random-order model allow us to circumvent the…

Data Structures and Algorithms · Computer Science 2025-11-11 Anupam Gupta , Marco Molinaro , Matteo Russo

When considering the number of subtrees of trees, the extremal structures which maximize this number among binary trees and trees with a given maximum degree lead to some interesting facts that correlate to other graphical indices in…

Combinatorics · Mathematics 2012-10-11 Xiu-Mei Zhang , Xiao-Dong Zhang , Daniel Gray , Hua Wang

We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called {em probabilistic arc consistency}, which is both a generalization of a well known algorithm for arc consistency used in…

Artificial Intelligence · Computer Science 2013-01-18 Michael C. Horsch , Bill Havens

Counterfactual explanations are usually generated through heuristics that are sensitive to the search's initial conditions. The absence of guarantees of performance and robustness hinders trustworthiness. In this paper, we take a…

Machine Learning · Computer Science 2021-06-28 Axel Parmentier , Thibaut Vidal

In this note we analyze the performance of a simple root-finding algorithm in uniform attachment trees. The leaf-stripping algorithm recursively removes all leaves of the tree for a carefully chosen number of rounds. We show that, with…

Probability · Mathematics 2024-10-10 Louigi Addario-Berry , Anna Brandenberger , Simon Briend , Nicolas Broutin , Gábor Lugosi

Cardinality constraints in optimization are commonly of $L^0$-type, and they lead to sparsely supported optimizers. An efficient way of dealing with these constraints algorithmically, when the objective functional is convex, is…

Optimization and Control · Mathematics 2026-02-26 Bastian Dittrich , Evelyn Herberg , Roland Herzog , Georg Müller

We give improved algorithms for maintaining edge-orientations of a fully-dynamic graph, such that the out-degree of each vertex is bounded. On one hand, we show how to orient the edges such that the out-degree of each vertex is proportional…

Data Structures and Algorithms · Computer Science 2023-02-16 Aleksander B. G. Christiansen , Jacob Holm , Ivor van der Hoog , Eva Rotenberg , Chris Schwiegelshohn