Who Solved the Secretary Problem
By Thomas S. Ferguson. 1989
Subfields: Game & Decision Theory, Algorithms & Complexity
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Game & Decision Theory
- Leon Ladewig
- Susanne Albers
- Fei Chen
- T-H. Hubert Chan
- Shaofeng H.-C. Jiang
- Peter M. Todd
- Kamal Kumar Jain
- Pedro Henrique de Oliveira Gomes
In Algorithms & Complexity
- Leon Ladewig
- Susanne Albers
- Peter M. Todd
- Kamal Kumar Jain
- Pedro Henrique de Oliveira Gomes
- J. Neil Bearden
- Haim Kaplan
- Bolin Ding
Citations in the corpus
- Unpacking the Exploration–Exploitation Tradeoff: A Synthesis of Human and Animal Literatures (2015, background): “…to take one (Fu & Gray, 2006), participants sampling from different options before deciding to choose one (Hertwig et al., 2004), or an employer interviewing potential candidates for a job as in the well-known secretary problem (also see Ferguson, 1989 for other types of optimal stopping problems).”
- New Results for the $k$-Secretary Problem (2020, background): “tatement of the problem dates back to the 1960s and the optimal algorithm was published by Lindley [1] and Dynkin [2]. For discussions on the origin of the problem, we refer to the survey by Ferguson [3]. In the past years, generalizations of the secretary problem involving selection of multiple ite”
- Prophet Secretary: Surpassing the 1-1/e Barrier (2017, background): “Another well known problem in the domain of optimal stopping is the Secretary problem [6, 9], where a set of values {x1, .”
- Bounding rationality to the world (2003, methodology): “(See Ferguson , 1989, for a review of the literature on the secretary problem and this optimal solution.)”
- A multi-attribute extension of the secretary problem: Theory and experiments (2004, methodology): “A historical review of the CSP can be found in Ferguson (1989) and in Samuels (1991). Depending on the context, the problem is sometimes referred to by other names (e.g., the ‘‘Sultan’s dowry’’ problem). Seale and Rapoport (1997) had subjects play a large number of random instances of the CSP in two”
- Secretary Problems via Linear Programming (2010, methodology): “We refer the reader to the survey by Ferguson [12] on the historical and extensive work on different variants of the secretary problem.”
- The structure of online diffusion networks (2012, background): “(3) The Secretary Game is an online variant of the secretary problem [Ferguson 1989], a sequential search game in which players attempt to .nd an optimal stopping rule.”
- Toward a Theory of Behavioral Operations (2008, background): “Lastly, OM researchers have used experiments to explore potential behavioral influences through the study of the “secretary problem” (Ferguson, 1988), a mathematics puzzle, suited to laboratory experiments, that represents a class of real-world sequential decision-making tasks.”
- Online mobile Micro-Task Allocation in spatial crowdsourcing (2016, methodology): “We next study the competitive ratio of TGOA, which is inspired by [35] and extended to our problem.”
- Revealing Optimal Thresholds for Generalized Secretary Problem via Continuous LP: Impacts on Online K-Item Auction and Bipartite K-Matching with Random Arrival Order (2015, background): “As described in the survey by Ferguson [7], the original secretary problem was posed such that an adversary chooses n weights as in the online auction, but the performance ratio of the algorithm is still the probability that the best item is selected.”
- Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks (2018, methodology): “More advanced techniques such as Secretary Problem [33] (by considering each learned policy as a secretary) can be used to decide”
- Automatic performance tuning of sparse matrix kernels (2003, background): “For instance, the early stopping problem can be posed as a similar problem which has been treated extensively in the statistical literature under the theory of optimal stopping [77, 115, 116].”