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Border's theorem gives an intuitive linear characterization of the feasible interim allocation rules of a Bayesian single-item environment, and it has several applications in economic and algorithmic mechanism design. All known…

Computer Science and Game Theory · Computer Science 2015-04-30 Parikshit Gopalan , Noam Nisan , Tim Roughgarden

This paper deals with (finite or infinite) sequences of arbitrary independent events in some probability space. We find sharp lower bounds for the probability of a union of such events when the sum of their probabilities is given. The…

Probability · Mathematics 2016-09-29 Jürgen Grahl , Shahar Nevo

Probabilities of causation play a crucial role in modern decision-making. Pearl defined three binary probabilities of causation, the probability of necessity and sufficiency (PNS), the probability of sufficiency (PS), and the probability of…

Artificial Intelligence · Computer Science 2022-10-18 Ang Li , Judea Pearl

We introduce a betting game, where the gambler aims to guess the last success epoch from past observed data. The player may bet on the event that no further successes occur, or choose a `trap' which is any span of future times. In the…

Probability · Mathematics 2024-06-25 Alexander Gnedin , Zakaria Derbazi

We study the properties of the free boundaries and the corresponding hitting times in the context of optimal stopping in discrete time. We first prove the continuity of the map from the boundaries to the expected value of the corresponding…

Probability · Mathematics 2025-04-16 H. Mete Soner , Valentin Tissot-Daguette

We study the (weak) equilibrium problem arising from the problem of optimally stopping a one-dimensional diffusion subject to an expectation constraint on the time until stopping. The weak equilibrium problem is realized with a set of…

Probability · Mathematics 2024-06-14 Sören Christensen , Maike Klein , Boy Schultz

We consider a randomized algorithm for the unique games problem, using independent multinomial probabilities to assign labels to the vertices of a graph. The expected value of the solution obtained by the algorithm is expressed as a…

Computational Complexity · Computer Science 2015-08-10 Rajeev Kohli , Ramesh Krishnamurti

In this article, a general problem of sequential statistical inference for general discrete-time stochastic processes is considered. The problem is to minimize an average sample number given that Bayesian risk due to incorrect decision does…

Statistics Theory · Mathematics 2010-10-18 Andrey Novikov

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

We analyze an optimal stopping problem with a series of inequality-type and equality-type expectation constraints in a general non-Markovian framework. We show that the optimal stopping problem with expectation constraints (OSEC) in an…

Optimization and Control · Mathematics 2023-02-10 Erhan Bayraktar , Song Yao

We consider the optimal double stopping time problem defined for each stopping time $S$ by $v(S)=\esssup\{E[\psi(\tau_1, \tau_2) | \F_S], \tau_1, \tau_2 \geq S \}$. Following the optimal one stopping time problem, we study the existence of…

Probability · Mathematics 2009-09-21 Magdalena Kobylanski , Marie-Claire Quenez , Elisabeth Rouy-Mironescu

Let $\mu$ be a probability measure on $\text{GL}_d(\mathbb{R})$ and denote by $S_n:= g_n \cdots g_1$ the associated random matrix product, where $g_j$ are i.i.d. with law $\mu$. Under the assumptions that $\mu$ has a finite exponential…

Probability · Mathematics 2023-02-06 Tien-Cuong Dinh , Lucas Kaufmann , Hao Wu

This work addresses the classic machine learning problem of online prediction with expert advice. We consider the finite-horizon version of this zero-sum, two-person game. Using verification arguments from optimal control theory, we view…

Machine Learning · Computer Science 2020-06-30 Vladimir A. Kobzar , Robert V. Kohn , Zhilei Wang

We study a mathematical model motivated by the support/resistance line method in technical analysis where the underlying stock price transitions between three states of nature in a path-dependent manner. For optimal stopping problems with…

Trading and Market Microstructure · Quantitative Finance 2025-04-15 Vicky Henderson , Saul Jacka , Ruiqi Liu , Jun Maeda

We study the stability of deterministic systems given sequences of large, jump-like perturbations. Our main result is to dervie a lower bound for the probability of the system to remain in the basin, given that perturbations are rare…

Chaotic Dynamics · Physics 2019-11-26 Paul Schultz , Frank Hellmann , Kevin N. Webster , Jürgen Kurths

In this paper, we consider a class of stochastic impulse control problem when there is a fixed delay $\Delta$ between the decision and execution times. The dynamics of the controlled system between two impulses is an arbitrary adapted…

Probability · Mathematics 2026-01-23 Said Hamadène , Ibtissam Hdhiri

It is often claimed that Bayesian methods, in particular Bayes factor methods for hypothesis testing, can deal with optional stopping. We first give an overview, using elementary probability theory, of three different mathematical meanings…

Statistics Theory · Mathematics 2021-03-24 Allard Hendriksen , Rianne de Heide , Peter Grünwald

In this paper, we establish sufficient conditions for the existence of error bounds at infinity for lower semicontinuous inequality systems. We also show that the existence of an error bound at infinity of constraint systems plays an…

Optimization and Control · Mathematics 2023-11-06 Nguyen Van Tuyen

We consider the problem of optimally stopping a Brownian bridge with an unknown pinning time so as to maximise the value of the process upon stopping. Adopting a Bayesian approach, we assume the stopper has a general continuous prior and is…

Probability · Mathematics 2020-03-17 Kristoffer Glover

An approach to reasoning with default rules where the proportion of exceptions, or more generally the probability of encountering an exception, can be at least roughly assessed is presented. It is based on local uncertainty propagation…

Artificial Intelligence · Computer Science 2013-03-26 Stephane Amarger , Didier Dubois , Henri Prade