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We give asymptotic lower bounds of the value for Bruss' optimal stopping problem with multiple stopping chances. It interestingly consists of the asymptotic threshold values in the optimal multiple stopping strategy. Another interesting…

Probability · Mathematics 2017-11-22 Tomomi Matsui , Katsunori Ano

We consider an original problem that arises from the issue of security analysis of a power system and that we name optimal discovery with probabilistic expert advice. We address it with an algorithm based on the optimistic paradigm and on…

Machine Learning · Computer Science 2013-04-02 Sebastien Bubeck , Damien Ernst , Aurelien Garivier

In the weighted bipartite matching problem, the goal is to find a maximum-weight matching in a bipartite graph with nonnegative edge weights. We consider its online version where the first vertex set is known beforehand, but vertices of the…

Computer Science and Game Theory · Computer Science 2021-03-05 Rebecca Reiffenhäuser

The task of learning to pick a single preferred example out a finite set of examples, an "optimal choice problem", is a supervised machine learning problem with complex, structured input. Problems of optimal choice emerge often in various…

Artificial Intelligence · Computer Science 2017-07-07 Marina Sapir

The secretary problem is a classic model for online decision making. Recently, combinatorial extensions such as matroid or matching secretary problems have become an important tool to study algorithmic problems in dynamic markets. Here the…

Data Structures and Algorithms · Computer Science 2017-08-28 Martin Hoefer , Bojana Kodric

Imagine a large firm with multiple departments that plans a large recruitment. Candidates arrive one-by-one, and for each candidate the firm decides, based on her data (CV, skills, experience, etc), whether to summon her for an interview.…

Machine Learning · Computer Science 2019-06-03 Alon Cohen , Avinatan Hassidim , Haim Kaplan , Yishay Mansour , Shay Moran

We study various generalizations of the secretary problem with submodular objective functions. Generally, a set of requests is revealed step-by-step to an algorithm in random order. For each request, one option has to be selected so as to…

Data Structures and Algorithms · Computer Science 2016-08-01 Thomas Kesselheim , Andreas Tönnis

Query expansion is a well known method to improve the performance of information retrieval systems. In this work we have tested different approaches to extract the candidate query terms from the top ranked documents returned by the…

Information Retrieval · Computer Science 2008-12-18 José R. Pérez-Agüera , Lourdes Araujo

Optimal stopping problems consider the question of deciding when to stop an observation-generating process in order to maximize a return. We examine the problem of simultaneously learning and planning in such domains, when data is collected…

Artificial Intelligence · Computer Science 2017-05-25 Karan Goel , Christoph Dann , Emma Brunskill

We study the classical problem of prediction with expert advice in the adversarial setting with a geometric stopping time. In 1965, Cover gave the optimal algorithm for the case of 2 experts. In this paper, we design the optimal algorithm,…

Machine Learning · Computer Science 2016-07-12 Nick Gravin , Yuval Peres , Balasubramanian Sivan

This paper studies Makespan Minimization in the secretary model. Formally, jobs, specified by their processing times, are presented in a uniformly random order. An online algorithm has to assign each job permanently and irrevocably to one…

Data Structures and Algorithms · Computer Science 2021-10-28 Susanne Albers , Maximilian Janke

We tackle the problem of Selective Classification where the objective is to achieve the best performance on a predetermined ratio (coverage) of the dataset. Recent state-of-the-art selective methods come with architectural changes either…

Machine Learning · Computer Science 2023-03-03 Leo Feng , Mohamed Osama Ahmed , Hossein Hajimirsadeghi , Amir Abdi

We consider the problem of a decision-maker searching for information on multiple alternatives when information is learned on all alternatives simultaneously. The decision-maker has a running cost of searching for information, and has to…

Theoretical Economics · Economics 2020-04-13 T. Tony Ke , Wenpin Tang , J. Miguel Villas-Boas , Yuming Zhang

In the secretary problem of Cayley (1875) and Moser (1956), $n$ non-negative, independent, random variables with common distribution are sequentially presented to a decision maker who decides when to stop and collect the most recent…

Probability · Mathematics 2019-10-22 Alessandro Arlotto , Itai Gurvich

In this paper, we aim at solving a class of multiple testing problems under the Bayesian sequential decision framework. Our motivating application comes from binary labeling tasks in crowdsourcing, where the requestor needs to…

Methodology · Statistics 2017-08-29 Xiaoou Li , Yunxiao Chen , Xi Chen , Jingchen Liu , Zhiliang Ying

What is the optimal order in which a researcher should submit their papers to journals of differing quality? I analyze a sequential search model without recall where the researcher's expected value from journal submission depends on the…

Theoretical Economics · Economics 2024-02-06 Daniel Luo

We study a problem when a solution to optimal stopping problem for one-dimensional diffusion will generate by threshold strategy. Namely, we give necessary and sufficient conditions under which an optimal stopping time can be specified as…

Probability · Mathematics 2013-06-20 V. I. Arkin , A. D. Slastnikov

The ranking problem is to order a collection of units by some unobserved parameter, based on observations from the associated distribution. This problem arises naturally in a number of contexts, such as business, where we may want to rank…

Statistics Theory · Mathematics 2019-09-04 Toby Kenney

We revisit three fundamental problems in algorithms under uncertainty: the Secretary Problem, Prophet Inequality, and Stochastic Probing, each subject to general downward-closed constraints. When elements have binary values, all three…

Data Structures and Algorithms · Computer Science 2026-04-02 Aviad Rubinstein , Sahil Singla

We consider the problem of ranking n experts based on their performances on d tasks. We make a monotonicity assumption stating that for each pair of experts, one outperforms the other on all tasks. We consider the sequential setting where…

Machine Learning · Statistics 2023-06-06 El Mehdi Saad , Nicolas Verzelen , Alexandra Carpentier