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We consider a discounted infinite horizon optimal stopping problem. If the underlying distribution is known a priori, the solution of this problem is obtained via dynamic programming (DP) and is given by a well known threshold rule. When…

Machine Learning · Computer Science 2021-02-23 Daniel Russo , Assaf Zeevi , Tianyi Zhang

We develop novel empirical Bernstein inequalities for the variance of bounded random variables. Our inequalities hold under constant conditional variance and mean, without further assumptions like independence or identical distribution of…

Statistics Theory · Mathematics 2026-05-28 Diego Martinez-Taboada , Aaditya Ramdas

We study best arm identification in a federated multi-armed bandit setting with a central server and multiple clients, when each client has access to a {\em subset} of arms and each arm yields independent Gaussian observations. The goal is…

Machine Learning · Computer Science 2023-12-20 Zhirui Chen , P. N. Karthik , Vincent Y. F. Tan , Yeow Meng Chee

We consider descending price auctions for selling $m$ units of a good to unit demand i.i.d. buyers where there is an exogenous bound of $k$ on the number of price levels the auction clock can take. The auctioneer's problem is to choose…

Computer Science and Game Theory · Computer Science 2022-03-04 Saeed Alaei , Ali Makhdoumi , Azarakhsh Malekian , Rad Niazadeh

We study the problem of testing discrete distributions with a focus on the high probability regime. Specifically, given samples from one or more discrete distributions, a property $\mathcal{P}$, and parameters $0< \epsilon, \delta <1$, we…

Data Structures and Algorithms · Computer Science 2020-09-15 Ilias Diakonikolas , Themis Gouleakis , Daniel M. Kane , John Peebles , Eric Price

In this paper, we study a remote monitoring system where a receiver observes a remote binary Markov source and decides whether to sample and transmit the state through a randomly delayed channel. We adopt uncertainty of information (UoI),…

Information Theory · Computer Science 2024-05-20 Xiaomeng Chen , Aimin Li , Shaohua Wu

The extreme statistics of time signals is studied when the maximum is measured from the initial value. In the case of independent, identically distributed (iid) variables, we classify the limiting distribution of the maximum according to…

Statistical Mechanics · Physics 2009-11-13 T. W. Burkhardt , G. Gyorgyi , N. R. Moloney , Z. Racz

We consider the problem of selecting sequentially a unimodal subsequence from a sequence of independent identically distributed random variables, and we find that a person doing optimal sequential selection does within a factor of the…

Probability · Mathematics 2011-10-31 Alessandro Arlotto , J. Michael Steele

Due to numerous applications in retail and (online) advertising the problem of assortment selection has been widely studied under many combinations of discrete choice models and feasibility constraints. In many situations, however, an…

Data Structures and Algorithms · Computer Science 2023-08-11 Vineet Goyal , Salal Humair , Orestis Papadigenopoulos , Assaf Zeevi

We study a fundamental stochastic selection problem involving $n$ independent random variables, each of which can be queried at some cost. Given a tolerance level $\delta$, the goal is to find a value that is $\delta$-approximately minimum…

Data Structures and Algorithms · Computer Science 2025-04-25 Hessa Al-Thani , Viswanath Nagarajan

We consider the problem of one-way communication when the recipient does not know exactly the distribution that the messages are drawn from, but has a "prior" distribution that is known to be close to the source distribution, a problem…

Information Theory · Computer Science 2018-11-26 Mark Braverman , Brendan Juba

An unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an $\alpha$-maxmin nonlinear…

Mathematical Finance · Quantitative Finance 2021-07-15 Yu-Jui Huang , Xiang Yu

We consider a class of time-inhomogeneous optimal stopping problems and we provide sufficient conditions on the data of the problem that guarantee monotonicity of the optimal stopping boundary. In our setting, time-inhomogeneity stems not…

Optimization and Control · Mathematics 2023-01-16 Alessandro Milazzo

Prophet inequalities and secretary problems have been extensively studied in recent years due to their elegance, connections to online algorithms, stochastic optimization, and mechanism design problems in game theoretic settings. Rubinstein…

Data Structures and Algorithms · Computer Science 2021-07-09 Chandra Chekuri , Vasilis Livanos

We address the problem of finding worst-case nonparametric bounds for T-statistic by considering the extremal problem of maximising the mid-quantile (a special case of 'smoothed quantile' as discussed in \cite{St77} and \cite{W11}) $\tilde…

Statistics Theory · Mathematics 2025-09-03 David Edelman

Consider a degree-$d$ polynomial $f(\xi_1,\dots,\xi_n)$ of independent Rademacher random variables $\xi_1,\dots,\xi_n$. To what extent can $f(\xi_1,\dots,\xi_n)$ concentrate on a single point? This is the so-called polynomial…

Combinatorics · Mathematics 2025-05-30 Zhihan Jin , Matthew Kwan , Lisa Sauermann , Yiting Wang

In this paper, we study the optimal stopping problem in the case where the reward is given by a family $(\phi(\tau ),\;\;\tau \in \stopo)$ of non negative random variables indexed by predictable stopping times. We treat the problem by means…

Probability · Mathematics 2018-12-06 Siham Bouhadou , Youssef Ouknine

Prophet inequalities are a useful tool for designing online allocation procedures and comparing their performance to the optimal offline allocation. In the basic setting of $k$-unit prophet inequalities, the well-known procedure of Alaei…

Computer Science and Game Theory · Computer Science 2023-10-10 Jiashuo Jiang , Will Ma , Jiawei Zhang

Fix some $n \in \mathbb{N}$ and let $X_1, X_2,\dots, X_n$ be independent random variables drawn from the uniform distribution on $[0,1]$. A decision maker is shown the variables sequentially and, after each observation, must decide whether…

Probability · Mathematics 2016-02-01 Rémi Dendievel , Yvik Swan

The problem of identifying the best arm among a collection of items having Gaussian rewards distribution is well understood when the variances are known. Despite its practical relevance for many applications, few works studied it for…

Machine Learning · Statistics 2023-01-24 Marc Jourdan , Rémy Degenne , Emilie Kaufmann