Secretary Problems via Linear Programming
By Niv Buchbinder, Kamal Kumar Jain, Mohit Singh. 2010
79 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Industrial and Manufacturing Engineering, Management Science and Operations Research, Optimization & Training, Game & Decision Theory
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Leon Ladewig
- Susanne Albers
- Simon Lacoste-Julien
- Pascal Vincent
- Renato Paes Leme
- Sergei Vassilvitskii
- Silvio Lattanzi
- Fei Chen
In Industrial and Manufacturing Engineering
- Leon Ladewig
- Simon Lacoste-Julien
- Susanne Albers
- Pascal Vincent
- Renato Paes Leme
- Sergei Vassilvitskii
- Silvio Lattanzi
- Fei Chen
In Management Science and Operations Research
- Leon Ladewig
- Susanne Albers
- Gauthier Gidel
- Simon Lacoste-Julien
- Pascal Vincent
- Renato Paes Leme
- Sergei Vassilvitskii
- Fei Chen
In Optimization & Training
- Gauthier Gidel
- Pascal Vincent
- Hugo Berard
- Simon Lacoste-Julien
- Avishek Joey Bose
- William L. Hamilton
- Andjela Mladenovic
- Leon Ladewig
In Game & Decision Theory
- Leon Ladewig
- Susanne Albers
- Simon Lacoste-Julien
- Pascal Vincent
- Fei Chen
- T-H. Hubert Chan
- Shaofeng H.-C. Jiang
- Hugo Berard
Citations in the corpus
- Online Adversarial Attacks (2021, background): “Most prominently, Buchbinder et al. [2014] and Chan et al. [2014] proved that the k-secretary problem can be solved optimally (in terms of competitive ratio) using linear programs (LPs), assuming a fixed length of n for the data stream.”
- New Results for the $k$-Secretary Problem (2020, methodology): “ch could be a key insight into the general case. From a technical point of view, we analyze the algorithms using basic combinatorial constructs exclusively. This is in contrast to previous approaches [14, 22] which can only be analyzed using heavyweight linear programming techniques. The combinatori”
- Secretaries with Advice (2020, methodology): “Our formulation generalize the linear program of Buchbinder, Jain, and Singh [7] to our more challenging setting.”
- Competitive Analysis with a Sample and the Secretary Problem (2019, unknown): “Overall we get (cid:0) (cid:1) We note that Theorem 3.8 can also be derived from the work of Buchbinder et al. [4], by including the constraint that the first h candidates must be rejected in the linear program that characterizes all algorithms for the secretary 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, methodology): “Buchbinder, Jain and Singh [4] considered the following generalized secretary problem.”