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How do decisions change with the economic environment and with time? This paper studies general nonstationary stopping problems and provides the methodological tools to answer these questions. First, we identify conditions that ensure a…

Theoretical Economics · Economics 2024-08-01 Théo Durandard , Matteo Camboni

Selective inference is a subfield of statistics that enables valid inference after selection of a data-dependent question. In this paper, we introduce selectively dominant p-values, a class of p-values that allow practitioners to easily…

Methodology · Statistics 2024-11-22 Anav Sood

This paper presents an axiomatic approach to finite Markov decision processes where the discount rate is zero. One of the principal difficulties in the no discounting case is that, even if attention is restricted to stationary policies, a…

Optimization and Control · Mathematics 2022-11-23 Adam Jonsson

We describe and develop a close relationship between two problems that have customarily been regarded as distinct: that of maximizing entropy, and that of minimizing worst-case expected loss. Using a formulation grounded in the equilibrium…

Statistics Theory · Mathematics 2007-06-13 Peter D. Grunwald , A. Philip Dawid

How can we monitor, in real time, whether one uncertain prospect has any upside over another? To answer this question, we develop a novel family of sequential, anytime-valid tests for stochastic dominance (SD; also known as stochastic…

Methodology · Statistics 2026-04-24 Sebastian Arnold , Yo Joong Choe , Marco Scarsini , Ilia Tsetlin

Capacitated Domination generalizes the classic Dominating Set problem by specifying for each vertex a required demand and an available capacity for covering demand in its closed neighborhood. The objective is to find a minimum-sized set of…

Data Structures and Algorithms · Computer Science 2016-04-19 Amariah Becker

The ability to uncover preferences from choices is fundamental for both positive economics and welfare analysis. Overwhelming evidence shows that choice is stochastic, which has given rise to random utility models as the dominant paradigm…

General Economics · Economics 2018-11-07 Carlos Alos-Ferrer , Ernst Fehr , Nick Netzer

Stochastic dominance is a technique for evaluating the performance of online algorithms that provides an intuitive, yet powerful stochastic order between the compared algorithms. Accordingly this holds for bijective analysis, which can be…

Data Structures and Algorithms · Computer Science 2016-07-22 Spyros Angelopoulos , Marc P. Renault , Pascal Schweitzer

A Peskun ordering between two samplers, implying a dominance of one over the other, is known among the Markov chain Monte Carlo community for being a remarkably strong result. It is however also known for being a result that is notably…

Computation · Statistics 2024-05-20 Philippe Gagnon , Florian Maire

A central challenge in statistical inference is the presence of confounding variables that may distort observed associations between treatment and outcome. Conventional "causal" methods, grounded in assumptions such as ignorability, exclude…

Methodology · Statistics 2025-09-09 Ellis Scharfenaker , Duncan K. Foley

Though learning has become a core component of modern information processing, there is now ample evidence that it can lead to biased, unsafe, and prejudiced systems. The need to impose requirements on learning is therefore paramount,…

Machine Learning · Computer Science 2022-10-20 Luiz F. O. Chamon , Santiago Paternain , Miguel Calvo-Fullana , Alejandro Ribeiro

In this paper we present two different results in the context of nonlinear analysis. The first one is essentially a nonlinear technique that, in view of its strong generality, may be useful in different practical problems. The second…

Functional Analysis · Mathematics 2015-10-02 Daniel Pellegrino , Joedson Santos , Juan B. Seoane-Sepúlveda

People are influenced by the choices of others, a phenomenon observed across contexts in the social and behavioral sciences. Social influence can lock in an initial popularity advantage of an option over a higher quality alternative. Yet…

Physics and Society · Physics 2024-08-09 Alexandros Gelastopoulos , Pantelis P. Analytis , Gaël Le Mens , Arnout van de Rijt

Rock is wrapped by paper, paper is cut by scissors, and scissors are crushed by rock. This simple game is popular among children and adults to decide on trivial disputes that have no obvious winner, but cyclic dominance is also at the heart…

We explored decision-making dynamics in social systems, referencing the 'herd behavior' from prior studies where individuals follow preceding choices without understanding the underlying reasons. While previous research highlighted a…

Artificial Intelligence · Computer Science 2023-12-29 Lu Li , Huangxing Li

In the best choice problem with random arrivals, an unknown number $n$ of rankable items arrive at times sampled from the uniform distribution. As is well known, a real-time player can ensure stopping at the overall best item with…

Probability · Mathematics 2021-03-09 Alexander Gnedin

This paper is devoted to the online dominating set problem and its variants. We believe the paper represents the first systematic study of the effect of two limitations of online algorithms: making irrevocable decisions while not knowing…

Data Structures and Algorithms · Computer Science 2018-09-14 Joan Boyar , Stephan J. Eidenbenz , Lene M. Favrholdt , Michal Kotrbčík , Kim S. Larsen

We discover the mechanism for the transition from self-segregation (into opposing groups) to clustering (towards cautious behaviors) in the evolutionary minority game (EMG). The mechanism is illustrated with a statistical mechanics analysis…

Condensed Matter · Physics 2013-05-29 Kan Chen , Bing-Hong Wang , Baosheng Yuan

The notion of path-complete $p$-dominance for switching linear systems (in short, path-dominance) is introduced as a way to generalize the notion of dominant/slow modes for LTI systems. Path-dominance is characterized by the contraction…

Optimization and Control · Mathematics 2018-08-30 Guillaume O. Berger , Fulvio Forni , Raphaël M. Jungers

The key distinguishing property of a Bayesian approach is marginalization instead of optimization, not the prior, or Bayes rule. Bayesian inference is especially compelling for deep neural networks. (1) Neural networks are typically…

Machine Learning · Computer Science 2020-01-30 Andrew Gordon Wilson
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