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The main result of this paper is a proof using real analysis of the monotonicity of the topological entropy for the family of quadratic maps, sometimes called Milnor's Monotonicity Conjecture. In contrast, the existing proofs rely in one…

Dynamical Systems · Mathematics 2020-10-13 José M. Amigó , Angel Giménez

This paper presents a simple algorithm to check whether reachability probabilities in parametric Markov chains are monotonic in (some of) the parameters. The idea is to construct - only using the graph structure of the Markov chain and…

Logic in Computer Science · Computer Science 2019-07-22 Jip Spel , Sebastian Junges , Joost-Pieter Katoen

Core stability is a natural and well-studied notion for group fairness in multi-winner voting, where the task is to select a committee from a pool of candidates. We study the setting where voters either approve or disapprove of each…

Computer Science and Game Theory · Computer Science 2025-12-19 Ratip Emin Berker , Emanuel Tewolde , Vincent Conitzer , Mingyu Guo , Marijn Heule , Lirong Xia

An important tool to quantify the likeness of two probability measures are f-divergences, which have seen widespread application in statistics and information theory. An example is the total variation, which plays an exceptional role among…

Probability · Mathematics 2009-03-11 Jochen Bröcker

Algorithms for min-max optimization and variational inequalities are often studied under monotonicity assumptions. Motivated by non-monotone machine learning applications, we follow the line of works [Diakonikolas et al., 2021, Lee and Kim,…

Optimization and Control · Mathematics 2023-07-19 Eduard Gorbunov , Adrien Taylor , Samuel Horváth , Gauthier Gidel

We study the problem of designing multiwinner voting rules that are candidate monotone and proportional. We show that the set of committees satisfying the proportionality axiom of proportionality for solid coalitions is candidate monotone.…

Computer Science and Game Theory · Computer Science 2025-12-05 Jannik Peters

A monotone grid class is a permutation class (i.e., a downset of permutations under the containment order) defined by local monotonicity conditions. We give a simplified proof of a result of Murphy and Vatter that monotone grid classes of…

Combinatorics · Mathematics 2010-07-08 Vincent Vatter , Steve Waton

Single-peakedness is one of the most important and well-known domain restrictions on preferences. The computational study of single-peaked electorates has largely been restricted to elections with tie-free votes, and recent work that…

Computer Science and Game Theory · Computer Science 2016-06-21 Zack Fitzsimmons , Edith Hemaspaandra

In this paper, we propose to study the following maximum ordinal consensus problem: Suppose we are given a metric system (M, X), which contains k metrics M = {\rho_1,..., \rho_k} defined on the same point set X. We aim to find a maximum…

Computational Complexity · Computer Science 2021-03-03 Dingkang Wang , Yusu Wang

We consider positive solutions, possibly unbounded, to the semilinear equation $-\Delta u=f(u)$ on continuous epigraphs bounded from below. Under the homogeneous Dirichlet boundary condition, we prove new monotonicity results for $u$, when…

Analysis of PDEs · Mathematics 2025-02-10 Nicolas Beuvin , Alberto Farina , Berardino Sciunzi

In this paper we consider the problem of uniformity testing with limited memory. We observe a sequence of independent identically distributed random variables drawn from a distribution $p$ over $[n]$, which is either uniform or is…

Information Theory · Computer Science 2022-06-22 Tomer Berg , Or Ordentlich , Ofer Shayevitz

We give several new characterizations of completely monotone functions and Bernstein functions via two approaches: the first one is driven algebraically via elementary preserving mappings and the second one is developed in terms of the…

Probability · Mathematics 2016-02-17 Rafik Aguech , Wissem Jedidi

This paper considers the problem of testing temporal homogeneity of $p$-dimensional population mean vectors from the repeated measurements of $n$ subjects over $T$ times. To cope with the challenges brought by high-dimensional longitudinal…

Methodology · Statistics 2016-08-29 Ping-Shou Zhong , Jun Li

Invariance-based randomization tests -- such as permutation tests, rotation tests, or sign changes -- are an important and widely used class of statistical methods. They allow drawing inferences under weak assumptions on the data…

Statistics Theory · Mathematics 2022-05-31 Edgar Dobriban

We consider the setting in which a strong binary instrument is available for a binary treatment. The traditional LATE approach assumes the monotonicity condition stating that there are no defiers (or compliers). Since this condition is not…

Econometrics · Economics 2021-03-25 Yinchu Zhu

In two-sided matching markets, ensuring both stability and strategy-proofness poses a significant challenge; it is impossible when agents' preferences are unrestricted. But what if agents' preferences have specific restricted structures?…

Theoretical Economics · Economics 2025-07-03 Pinaki Mandal

Equivalent conditions that make the normal cone maximal monotone are investigated in the general settings of locally convex spaces. Some consequences such as Bishop Phelps and sum representability results are presented in the last part.

Functional Analysis · Mathematics 2019-01-24 M. D. Voisei

We theoretically analyze the problem of testing for $p$-hacking based on distributions of $p$-values across multiple studies. We provide general results for when such distributions have testable restrictions (are non-increasing) under the…

Econometrics · Economics 2022-05-13 Graham Elliott , Nikolay Kudrin , Kaspar Wuthrich

In the study of the behavior of centrality measures with respect to network modifications, score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc…

Social and Information Networks · Computer Science 2023-11-30 Paolo Boldi , Davide D'Ascenzo , Flavio Furia , Sebastiano Vigna

High complexity models are notorious in machine learning for overfitting, a phenomenon in which models well represent data but fail to generalize an underlying data generating process. A typical procedure for circumventing overfitting…

Machine Learning · Statistics 2025-03-11 James Schmidt
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