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Econometricians have usefully separated study of estimation into identification and statistical components. Identification analysis, which assumes knowledge of the probability distribution generating observable data, places an upper bound…

Econometrics · Economics 2025-09-03 Charles F. Manski

This is a comment on arXiv:2202.01553. In regression Gaussian covariate p-values (Davies and D{\"u}mbgen, arXiv:2202.01553) are used to control greedy forward subset selection by accounting for choosing the best when fitting many variables.…

Methodology · Statistics 2025-03-18 Joe Whittaker

Estimates of the approximate factor model are increasingly used in empirical work. Their theoretical properties, studied some twenty years ago, also laid the ground work for analysis on large dimensional panel data models with cross-section…

Econometrics · Economics 2020-08-04 Jushan Bai , Serena Ng

This paper considers the scenario in which there are multiple institutions, each with a limited capacity for candidates, and candidates, each with preferences over the institutions. A central entity evaluates the utility of each candidate…

Data Structures and Algorithms · Computer Science 2024-09-10 L. Elisa Celis , Amit Kumar , Nisheeth K. Vishnoi , Andrew Xu

Whether it be in normal form games, or in fair allocations, or in voter preferences in voting systems, a certain pattern of reasoning is common. From a particular profile, an agent or a group of agents may have an incentive to shift to a…

Computer Science and Game Theory · Computer Science 2019-07-23 Ramit Das , R. Ramanujam , Sunil Simon

Showing that the Ramsey property holds for a class of finite structures can be an extremely challenging task and a slew of sophisticated methods have been proposed in literature. In this paper we propose a new strategy to show that a class…

Combinatorics · Mathematics 2018-01-30 Dragan Masulovic

In many social-choice mechanisms the resulting choice is not the most preferred one for some of the participants, thus the need for methods to justify the choice made in a way that improves the acceptance and satisfaction of said…

Computer Science and Game Theory · Computer Science 2022-06-01 Sharadhi Alape Suryanarayana , David Sarne , Sarit Kraus

We present a general theoretical analysis of structured prediction with a series of new results. We give new data-dependent margin guarantees for structured prediction for a very wide family of loss functions and a general family of…

Machine Learning · Statistics 2016-12-02 Corinna Cortes , Mehryar Mohri , Vitaly Kuznetsov , Scott Yang

We consider a setting where in a known future time, a certain continuous random variable will be realized. There is a public prediction that gradually converges to its realized value, and an expert that has access to a more accurate…

Computer Science and Game Theory · Computer Science 2016-05-25 Amir Ban , Yossi Azar , Yishay Mansour

Voting and assignment are two of the most fundamental settings in social choice theory. For both settings, random serial dictatorship (RSD) is a well-known rule that satisfies anonymity, ex post efficiency, and strategyproofness. Recently,…

Computer Science and Game Theory · Computer Science 2014-08-05 Haris Aziz , Julián Mestre

We propose multi-type probabilistic serial (MPS) and multi-type random priority (MRP) as extensions of the well known PS and RP mechanisms to the multi-type resource allocation problem (MTRA) with partial preferences. In our setting, there…

Artificial Intelligence · Computer Science 2020-10-30 Haibin Wang , Sujoy Sikdar , Xiaoxi Guo , Lirong Xia , Yongzhi Cao , Hanpin Wang

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov…

Probability · Mathematics 2008-06-24 Lasse Leskelä

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola

This text presents an unified approach of probability and statistics in the pursuit of understanding and computation of randomness in engineering or physical or social system with prediction with generalizability. Starting from elementary…

History and Overview · Mathematics 2024-01-19 Lakshman Mahto

The well-studied problem of statistical rank aggregation has been applied to comparing sports teams, information retrieval, and most recently to data generated by human judgment. Such human-generated rankings may be substantially different…

Information Retrieval · Computer Science 2014-11-05 Andrew Mao , Hossein Azari Soufiani , Yiling Chen , David C. Parkes

How do we compare between hypotheses that are entirely consistent with observations? The marginal likelihood (aka Bayesian evidence), which represents the probability of generating our observations from a prior, provides a distinctive…

Machine Learning · Computer Science 2023-05-03 Sanae Lotfi , Pavel Izmailov , Gregory Benton , Micah Goldblum , Andrew Gordon Wilson

We present a new strategic voting model where we use uncertainty representation to model preferences. Specifically, we use probability sets as uncertainty representations, together with lower and upper expected utility gains to take…

Computer Science and Game Theory · Computer Science 2026-05-18 Henri Surugue , Sébastien Destercke

Given two families of continuous functions $u$ and $v$ on a topological space $X$, we define a preorder $R=R(u,v)$ on $X$ by the condition that any member of $u$ is an $R$-increasing and any member of $v$ is an $R$-decreasing function. It…

Optimization and Control · Mathematics 2016-01-05 Valentin Vankov Iliev

Human preferences are not always represented via complete linear orders: It is natural to employ partially-ordered preferences for expressing incomparable outcomes. In this work, we consider decision-making and probabilistic planning in…

Robotics · Computer Science 2024-10-21 Hazhar Rahmani , Abhishek N. Kulkarni , Jie Fu

We study the problem of assigning indivisible objects to agents where each is to receive at most one. To ensure fairness in the absence of monetary compensation, we consider random assignments. Random Priority, also known as Random Serial…

Theoretical Economics · Economics 2025-06-24 Christian Basteck
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