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Fantasy basketball has a rich underlying mathematical structure which makes optimal drafting strategy unclear. A central issue for category leagues is how to aggregate a player's statistics from all categories into a single number…

Methodology · Statistics 2024-09-10 Zach Rosenof

Performance measurement in competitive domains is frequently confounded by shared environmental factors that obscure true performance differences. For instance, absolute metrics can be heavily influenced by factors as varied as weather…

Data Analysis, Statistics and Probability · Physics 2025-04-29 M. R. Brown , G. Scott , L. Kilduff

We introduce a new preference-based framework for conditional treatment effect estimation and policy learning, built on the Conditional Preference-based Treatment Effect (CPTE). CPTE requires only that outcomes be ranked under a preference…

Machine Learning · Statistics 2026-02-04 Dovid Parnas , Mathieu Even , Julie Josse , Uri Shalit

We introduce the notion of linearly representable games. Broadly speaking, these are TU games that can be described by as many parameters as the number of players, like weighted voting games, airport games, or bankruptcy games. We show that…

Computer Science and Game Theory · Computer Science 2024-11-11 Ferenc Illés

Many models from a variety of areas involve the computation of an equilibrium or fixed point of some kind. Examples include Nash equilibria in games; market equilibria; computing optimal strategies and the values of competitive games…

Computational Complexity · Computer Science 2008-02-21 Mihalis Yannakakis

Following the risk-taking model of Seel and Strack, $n$ players decide when to stop privately observed Brownian motions with drift and absorption at zero. They are then ranked according to their level of stopping and paid a rank-dependent…

Optimization and Control · Mathematics 2021-11-09 Marcel Nutz , Yuchong Zhang

In team sports, traditional ranking statistics do not allow for the simultaneous evaluation of both individuals and combinations of players. Metrics for individual player rankings often fail to include the interaction effects between groups…

Methodology · Statistics 2025-05-09 Nathaniel Josephs , Elizabeth Upton

Benchmarking is a common method for evaluating trajectory prediction models for autonomous driving. Existing benchmarks rely on datasets, which are biased towards more common scenarios, such as cruising, and distance-based metrics that are…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Changhe Chen , Mozhgan Pourkeshavarz , Amir Rasouli

We apply Blackwell optimality to repeated games. An equilibrium whose strategy profile is sequentially rational for all high enough discount factors simultaneously is a Blackwell (subgame-perfect, perfect public, etc.) equilibrium. The bite…

Theoretical Economics · Economics 2025-01-13 Costas Cavounidis , Sambuddha Ghosh , Johannes Hörner , Eilon Solan , Satoru Takahashi

Peer-prediction is a mechanism which elicits privately-held, non-variable information from self-interested agents---formally, truth-telling is a strict Bayes Nash equilibrium of the mechanism. The original Peer-prediction mechanism suffers…

Computer Science and Game Theory · Computer Science 2016-03-28 Yuqing Kong , Grant Schoenebeck

Performative Reinforcement Learning (PRL) refers to a scenario in which the deployed policy changes the reward and transition dynamics of the underlying environment. In this work, we study multi-agent PRL by incorporating performative…

Machine Learning · Computer Science 2025-04-30 Rilind Sahitaj , Paulius Sasnauskas , Yiğit Yalın , Debmalya Mandal , Goran Radanović

Benchmarks for the evaluation of model performance play an important role in machine learning. However, there is no established way to describe and create new benchmarks. What is more, the most common benchmarks use performance measures…

Machine Learning · Computer Science 2022-09-23 Alicja Gosiewska , Katarzyna Woźnica , Przemysław Biecek

In a decision-making scenario, a principal could use conditional predictions from an expert agent to inform their choice. However, this approach would introduce a fundamental conflict of interest. An agent optimizing for predictive accuracy…

Machine Learning · Computer Science 2024-12-31 Rubi Hudson

We frame the meta-learning of prediction procedures as a search for an optimal strategy in a two-player game. In this game, Nature selects a prior over distributions that generate labeled data consisting of features and an associated…

Machine Learning · Statistics 2020-09-29 Alex Luedtke , Incheoul Chung , Oleg Sofrygin

Multi-round competitions often double or triple the points awarded in the final round, calling it a bonus, to maximize spectators' excitement. In a two-player competition with $n$ rounds, we aim to derive the optimal bonus size to maximize…

Computer Science and Game Theory · Computer Science 2024-06-10 Zhihuan Huang , Yuqing Kong , Tracy Xiao Liu , Grant Schoenebeck , Shengwei Xu

Quantilized mean-field game models involve quantiles of the population's distribution. We study a class of such games with a capacity for ranking games, where the performance of each agent is evaluated based on its terminal state relative…

Optimization and Control · Mathematics 2025-07-02 Rinel Foguen Tchuendom , Dena Firoozi , Michèle Breton

Evaluating the overall ability of players in the National Hockey League (NHL) is a difficult task. Existing methods such as the famous "plus/minus" statistic have many shortcomings. Standard linear regression methods work well when player…

Applications · Statistics 2013-03-01 A. C. Thomas , Samuel L. Ventura , Shane Jensen , Stephen Ma

An extensive literature in economics and social science addresses contests, in which players compete to outperform each other on some measurable criterion, often referred to as a player's score, or output. Players incur costs that are an…

Computer Science and Game Theory · Computer Science 2013-08-01 Leslie Ann Goldberg , Paul W. Goldberg , Piotr Krysta , Carmine Ventre

In this paper, we study the problem of fair classification in the presence of prior probability shifts, where the training set distribution differs from the test set. This phenomenon can be observed in the yearly records of several…

Machine Learning · Computer Science 2020-05-08 Arpita Biswas , Suvam Mukherjee

A myriad of different data are generated to characterize a soccer match. Here we discuss which performance indicators are particularly helpful to forecast the future results of a team via an estimation of the underlying team strengths with…

Physics and Society · Physics 2020-03-10 Andreas Heuer
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