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Monte Carlo (MC) simulations of many systems, in particular those with conflicting constraints, can be considerably speeded up by using multicanonical or related methods. Some of these approaches sample with a-priori unknown weight factors.…

High Energy Physics - Lattice · Physics 2009-10-30 Bernd A. Berg

The power of multiple testing procedures can be increased by using weighted p-values (Genovese, Roeder and Wasserman 2005). We derive the optimal weights and we show that the power is remarkably robust to misspecification of these weights.…

Statistics Theory · Mathematics 2007-06-13 Larry Wasserman , Kathryn Roeder

Efficiency is a core concept of multi-objective optimization problems and multi-attribute decision making. In the case of pairwise comparison matrices a weight vector is called efficient if the approximations of the elements of the pairwise…

Optimization and Control · Mathematics 2018-09-12 Kristóf Ábele-Nagy , Sándor Bozóki , Örs Rebák

In this paper we study the problem of making predictions using multiple structural casual models defined by different agents, under the constraint that the prediction satisfies the criterion of counterfactual fairness. Relying on the…

Artificial Intelligence · Computer Science 2021-05-25 Fabio Massimo Zennaro , Magdalena Ivanovska

We study the control complexity of fallback voting. Like manipulation and bribery, electoral control describes ways of changing the outcome of an election; unlike manipulation or bribery attempts, control actions---such as…

Computer Science and Game Theory · Computer Science 2010-04-21 Gábor Erdélyi , Lena Piras , Jörg Rothe

In the leader-follower approach, one or more agents are selected as leaders who do not change their states or have autonomous dynamics and can influence other agents, while the other agents, called followers, perform a simple protocol based…

Optimization and Control · Mathematics 2019-12-03 Natalia Basimova , Pavel Chebotarev

Alongside consistency, completeness of information is one of the key factors influencing data quality. The objective of this paper is to define ways of treating missing entries in pairwise comparisons (PC) method with respect to…

Discrete Mathematics · Computer Science 2019-11-25 Konrad Kułakowski , Anna Prusak , Jacek Szybowski

There are many priority deriving methods for pairwise comparison matrices. It is known that when these matrices are consistent all these methods result in the same priority vector. However, when they are inconsistent, the results may vary.…

Discrete Mathematics · Computer Science 2021-12-21 Konrad Kułakowski , Jiří Mazurek , Michał Strada

Statistical matching is an effective method for estimating causal effects in which treated units are paired with control units with ``similar'' values of confounding covariates prior to performing estimation. In this way, matching helps…

Methodology · Statistics 2023-09-13 Sanjeewani Weerasingha , Michael J. Higgins

Order matching systems form the backbone of modern equity exchanges, used by millions of investors daily. Thus, their operation is strictly controlled through numerous regulatory directives to ensure that markets are fair and transparent.…

Trading and Market Microstructure · Quantitative Finance 2019-04-01 Vasilios Mavroudis

While data science is battling to extract information from the enormous explosion of data, many estimators and algorithms are being developed for better prediction. Researchers and data scientists often introduce new methods and evaluate…

Applications · Statistics 2019-05-22 Raju Rimal , Trygve Almøy , Solve Sæbø

A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions, and hence have become targets of manipulation by unscrupulous vendors. We provide…

Machine Learning · Computer Science 2009-04-19 Xiang Yan , Benjamin Van Roy

In a recently introduced model of successive committee elections (Bredereck et al., AAAI-20) for a given set of ordinal or approval preferences one aims to find a sequence of a given length of "best" same-size committees such that each…

Computer Science and Game Theory · Computer Science 2025-05-27 Pallavi Jain , Andrzej Kaczmarczyk

Social networks are increasingly being used to conduct polls. We introduce a simple model of such social polling. We suppose agents vote sequentially, but the order in which agents choose to vote is not necessarily fixed. We also suppose…

Computer Science and Game Theory · Computer Science 2013-02-08 Serge Gaspers , Victor Naroditskiy , Nina Narodytska , Toby Walsh

This paper describes a generalizable model evaluation method that can be adapted to evaluate AI/ML models across multiple criteria including core scientific principles and more practical outcomes. Emerging from prediction competitions in…

Machine Learning · Computer Science 2024-03-19 Jason L. Harman , Jaelle Scheuerman

Top Two algorithms arose as an adaptation of Thompson sampling to best arm identification in multi-armed bandit models (Russo, 2016), for parametric families of arms. They select the next arm to sample from by randomizing among two…

Machine Learning · Statistics 2022-10-05 Marc Jourdan , Rémy Degenne , Dorian Baudry , Rianne de Heide , Emilie Kaufmann

In this paper we extend the principle of proportional representation to rankings. We consider the setting where alternatives need to be ranked based on approval preferences. In this setting, proportional representation requires that…

Computer Science and Game Theory · Computer Science 2016-12-06 Piotr Skowron , Martin Lackner , Markus Brill , Dominik Peters , Edith Elkind

Most social choice rules assume access to full rankings, while current alignment practice -- despite aiming for diversity -- typically treats voters as anonymous and comparisons as independent, effectively extracting only about one bit per…

Computer Science and Game Theory · Computer Science 2026-03-23 Luise Ge , Daniel Halpern , Gregory Kehne , Yevgeniy Vorobeychik

Since the Fourth Industrial Revolution, AI technology has been widely used in many fields, but there are several limitations that need to be overcome, including overfitting/underfitting, class imbalance, and the limitations of…

Machine Learning · Computer Science 2025-08-18 DongSeong-Yoon

In an online decision problem, one makes decisions often with a pool of decision sequence called experts but without knowledge of the future. After each step, one pays a cost based on the decision and observed rate. One reasonal goal would…

Machine Learning · Computer Science 2015-12-23 Chunyang Xiao