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We consider sequential selection of an alternating subsequence from a sequence of independent, identically distributed, continuous random variables, and we determine the exact asymptotic behavior of an optimal sequentially selected…

Probability · Mathematics 2011-08-15 Alessandro Arlotto , Robert W. Chen , Lawrence A. Shepp , J. Michael Steele

We find a two term asymptotic expansion for the optimal expected value of a sequentially selected monotone subsequence from a random permutation of length n. A striking feature of this expansion is that tells us that the expected value of…

Probability · Mathematics 2015-09-16 Peichao Peng , J. Michael Steele

In this paper we develop a unified approach for solving a wide class of sequential selection problems. This class includes, but is not limited to, selection problems with no-information, rank-dependent rewards, and considers both fixed as…

Probability · Mathematics 2020-01-27 Alexander Goldenshluger , Yaakov Malinovsky , Assaf Zeevi

In our problem, we are given access to a number of sequences of nonnegative i.i.d. random variables, whose realizations are observed sequentially. All sequences are of the same finite length. The goal is to pick one element from each…

Statistics Theory · Mathematics 2024-02-06 Aristomenis Tsopelakos , Olgica Milenkovic

We analyze the optimal policy for the sequential selection of an alternating subsequence from a sequence of $n$ independent observations from a continuous distribution $F$, and we prove a central limit theorem for the number of selections…

Probability · Mathematics 2016-09-05 Alessandro Arlotto , J. Michael Steele

This paper addresses the problem of sequential submodular maximization: selecting and ranking items in a sequence to optimize some composite submodular function. In contrast to most of the previous works, which assume access to the utility…

Machine Learning · Computer Science 2024-09-10 Jing Yuan , Shaojie Tang

In a prophet inequality problem, $n$ independent random variables are presented to a gambler one by one. The gambler decides when to stop the sequence and obtains the most recent value as reward. We evaluate a stopping rule by the…

Data Structures and Algorithms · Computer Science 2023-11-16 Andrés Cristi , Bruno Ziliotto

We consider the problem of sequencing a set of positive numbers. We try to find the optimal sequence to maximize the variance of its partial sums. The optimal sequence is shown to have a beautiful structure. It is interesting to note that…

Combinatorics · Mathematics 2012-02-14 Li Wei , Wangdong Qi , Dingxing Chen , Peng Liu , En Yuan

We model the joint distribution of choice probabilities and decision times in binary choice tasks as the solution to a problem of optimal sequential sampling, where the agent is uncertain of the utility of each action and pays a constant…

Neurons and Cognition · Quantitative Biology 2015-05-14 Drew Fudenberg , Philipp Strack , Tomasz Strzalecki

The problem of sequential anomaly detection is considered, where multiple data sources are monitored in real time and the goal is to identify the "anomalous" ones among them, when it is not possible to sample all sources at all times. A…

Statistics Theory · Mathematics 2022-05-23 Aristomenis Tsopelakos , Georgios Fellouris

We take a unifying approach to single selection optimal stopping problems with random arrival order and independent sampling of items. In the problem we consider, a decision maker (DM) initially gets to sample each of $N$ items…

Computer Science and Game Theory · Computer Science 2021-08-11 José Correa , Andrés Cristi , Boris Epstein , José Soto

Consider a sequence of $n$ independent random variables with a common continuous distribution $F$, and consider the task of choosing an increasing subsequence where the observations are revealed sequentially and where an observation must be…

Probability · Mathematics 2016-08-02 Alessandro Arlotto , Vinh V. Nguyen , J. Michael Steele

Sequential sampling occurs when the entire population is not known in advance and data are obtained one at a time or in groups of units. This manuscript proposes a new algorithm to sequentially select a balanced sample. The algorithm…

Methodology · Statistics 2023-01-04 Raphaël Jauslin , Bardia Panahbehagh , Yves Tillé

The decision-maker (DM) sequentially evaluates up to N of different, rankable options. DM must select exactly the best one at the moment of its appearance. In the process of searching, DM finds out with each applicant whether she is the…

Optimization and Control · Mathematics 2022-05-23 Krzysztof J. Szajowski

Finding the underlying probability distributions of a set of observed sequences under the constraint that each sequence is generated i.i.d by a distinct distribution is considered. The number of distributions, and hence the number of…

Information Theory · Computer Science 2018-10-16 Sara Shahi , Daniela Tuninetti , Natasha Devroye

We consider the problem of simultaneous detection and estimation under a sequential framework. In particular we are interested in sequential tests that distinguish between the null and the alternative hypothesis and every time the decision…

Statistics Theory · Mathematics 2013-09-24 Yasin Yilmaz , George V. Moustakides , Xiaodong Wang

We study the problem of optimal subset selection from a set of correlated random variables. In particular, we consider the associated combinatorial optimization problem of maximizing the determinant of a symmetric positive definite matrix…

Computation · Statistics 2019-07-12 Yu Wang , Nhu D. Le , James V. Zidek

The problem of simultaneously testing the marginal distributions of sequentially monitored, independent data streams is considered. The decisions for the various testing problems can be made at different times, using data from all streams,…

Methodology · Statistics 2023-04-21 Yiming Xing , Georgios Fellouris

In this paper, we study a fundamental problem in submodular optimization, which is called sequential submodular maximization. Specifically, we aim to select and rank a group of $k$ items from a ground set $V$ such that the weighted…

Machine Learning · Computer Science 2023-12-13 Shaojie Tang , Jing Yuan

We study the problem of selecting most informative subset of a large observation set to enable accurate estimation of unknown parameters. This problem arises in a variety of settings in machine learning and signal processing including…

Signal Processing · Electrical Eng. & Systems 2019-05-27 Abolfazl Hashemi , Mahsa Ghasemi , Haris Vikalo , Ufuk Topcu
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