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We compute exact second-order asymptotics for the cost of an optimal solution to the entropic optimal transport problem in the continuous-to-discrete, or semi-discrete, setting. In contrast to the discrete-discrete or continuous-continuous…

Optimization and Control · Mathematics 2022-03-17 Jason M. Altschuler , Jonathan Niles-Weed , Austin J. Stromme

A convenient framework for dealing with asymptotic limit problems of probabilistic nature is provided. These problems include questions such as finding the asymptotic proportion of terms of a sequence falling inside a given interval, or the…

History and Overview · Mathematics 2024-04-08 Michaël Bensimhoun

We consider a broad class of permutation invariant statistical problems by extending the standard decision theoretic definition to allow also selective inference tasks, where the target is specified only after seeing the data. For any such…

Statistics Theory · Mathematics 2025-02-06 Asaf Weinstein

Our purpose is to study a particular class of optimal stopping problems for Markov processes. We justify the value function convexity and we deduce that there exists a boundary function such that the smallest optimal stopping time is the…

Probability · Mathematics 2013-07-22 Diana Dorobantu

We consider two variants of the secretary problem, the\emph{ Best-or-Worst} and the \emph{Postdoc} problems, which are closely related. First, we prove that both variants, in their standard form with binary payoff 1 or 0, share the same…

Probability · Mathematics 2017-06-23 L. Bayon , P. Fortuny Ayuso , J. M. Grau , A. M. Oller-Marcen , M. M. Ruiz

The problem of pricing Bermudan options using Monte Carlo and a nonparametric regression is considered. We derive optimal non-asymptotic bounds for a lower biased estimate based on the suboptimal stopping rule constructed using some…

Pricing of Securities · Quantitative Finance 2009-08-03 Denis Belomestny

The last success problem is an optimal stopping problem that aims to maximize the probability of stopping on the last success in a sequence of independent $n$ Bernoulli trials. In the classical setting where complete information about the…

Probability · Mathematics 2024-07-24 Toru Yoshinaga , Yasushi Kawase

We introduce a novel extension of the canonical multi-armed bandit problem that incorporates an additional strategic innovation: abstention. In this enhanced framework, the agent is not only tasked with selecting an arm at each time step,…

Machine Learning · Computer Science 2026-03-24 Junwen Yang , Tianyuan Jin , Vincent Y. F. Tan

For the zone of moderate deviation probabilities the local asymptotic minimax lower bound of asymptotic efficiency of estimators is established. The estimation parameter is multidimensional. The lower bound admits the interpretation as the…

Statistics Theory · Mathematics 2012-06-08 Mikhail Ermakov

We consider the best-choice problem for independent (not necessarily iid) observations $X_1, \cdots, X_n$ with the aim of selecting the sample minimum. We show that in this full generality the monotone case of optimal stopping holds and the…

Probability · Mathematics 2021-10-13 Alexander Gnedin , Patryk Kozieł , Małgorzata Sulkowska

We study the optimal multiple stopping time problem defined for each stopping time $S$ by $v(S)=\operatorname {ess}\sup_{\tau_1,...,\tau_d\geq S}E[\psi(\tau_1,...,\tau_d)|\mathcal{F}_S]$. The key point is the construction of a new reward…

Probability · Mathematics 2011-08-30 Magdalena Kobylanski , Marie-Claire Quenez , Elisabeth Rouy-Mironescu

We prove non-asymptotic lower bounds on the expectation of the maximum of $d$ independent Gaussian variables and the expectation of the maximum of $d$ independent symmetric random walks. Both lower bounds recover the optimal leading…

Machine Learning · Statistics 2015-11-09 Francesco Orabona , David Pal

In this paper we consider stopping problems with partial observation under a general risk-sensitive optimization criterion for problems with finite and infinite time horizon. Our aim is to maximize the certainty equivalent of the stopping…

Optimization and Control · Mathematics 2017-03-29 Nicole Bäuerle , Ulrich Rieder

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Levy process. This allows the model to…

Optimization and Control · Mathematics 2014-09-23 Kazutoshi Yamazaki

We use probabilistic methods to characterise time dependent optimal stopping boundaries in a problem of multiple optimal stopping on a finite time horizon. Motivated by financial applications we consider a payoff of immediate stopping of…

Optimization and Control · Mathematics 2017-01-10 Tiziano De Angelis , Yerkin Kitapbayev

We prove the -- to the best knowledge of the authors -- first result on the fine asymptotic behavior of the regular part of the free boundary of the obstacle problem close to singularities. The result is motivated by our recent partial…

Analysis of PDEs · Mathematics 2023-10-18 Simon Eberle , Henrik Shahgholian , Georg Sebastian Weiss

We present a methodology for bounding the error term of an asymptotic solution to a singularly perturbed optimal control (SPOC) problem whose exact solution is known to be computationally intractable. In previous works, reduced or…

Optimization and Control · Mathematics 2016-10-20 Sei Howe , Panos Parpas

We consider a general problem of finding a strategy that minimizes the exponential moment of a given cost function, with an emphasis on its relation to the more common criterion of minimization the expectation of the first moment of the…

Information Theory · Computer Science 2011-03-16 Neri Merhav

We establish the validity of asymptotic limits for the general transportation problem between random i.i.d. points and their common distribution, with respect to the squared Euclidean distance cost, in any dimension larger than three.…

Probability · Mathematics 2025-02-18 Martin Huesmann , Michael Goldman , Dario Trevisan

We develop methods to solve general optimal stopping problems with opportunities to stop that arrive randomly. Such problems occur naturally in applications with market frictions. Pivotal to our approach is that our methods operate on…