RANDOMIZED ALLOCATION WITH NONPARAMETRIC ESTIMATION FOR A MULTI-ARMED BANDIT PROBLEM WITH COVARIATES

By Yuhong Yang, Dan Zhu. 2002

116 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4af9104d10a244a93ff08773d14dc3a3f2491329

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Vianney Perchet
2. Lauren Hannah
3. Warrren B Powell
4. David B. Dunson
5. Philippe Rigollet
6. Alexander Goldenshluger
7. Nicos G. Pavlidis
8. Dimitris K. Tasoulis

In Management Science and Operations Research

1. Vianney Perchet
2. Warrren B Powell
3. David B. Dunson
4. Lauren Hannah
5. Philippe Rigollet
6. Alexander Goldenshluger
7. Nicos G. Pavlidis
8. Dimitris K. Tasoulis

Citations in the corpus

• Woodroofe's One-Armed Bandit Problem Revisited (2009, unknown): “We refer to Woodroofe (1982), Clayton (1989), Yang and Zhu (2002), Wang, Kulkarni and Poor (2005) and Goldenshluger and Zeevi (2008), where further references can be found.”
• Semiconvex Regression for Metamodeling-Based Optimization (2014, methodology): “Estimation methods include linear combinations of basis functions [44], discretization the state space [56], random histograms, nearest neighbors [76] or adaptive partitioning [66].”
• Nonparametric Bandits with Covariates (2010, background): “to the studyof such banditproblems, as well as references therein for further links to antecedent literature. The first work to venture outside the realm of parametric modeling assumptions was that of Yang and Zhu (2002). In particular, they assumed the mean response in each arm, conditional on the c”
• A Linear Response Bandit Problem (2013, methodology): “We also refer the interested reader to Ginebra and Clayton (1995), Yang and Zhu (2002), Wang et al.]”
• Optimistic Bayesian Sampling in Contextual-Bandit Problems (2012, methodology): “We prove that, under unrestrictive assumptions, both approaches result in optimal behaviour in the long term consistency sense described by Yang and Zhu (2002).”
• Simulation Studies of Multi-armed Bandits with Covariates (Invited Paper) (2008, methodology): “The multi-armed bandit problem with continuous covariates has been investigated by Yang and Zhu [11].”
• A modern Bayesian look at the multi-armed bandit (2010, background): “Yang and Zhu [23] proved that an -decreasing randomization can restore consistency to a greedy policy.”
• The multi-armed bandit problem with covariates (2011, background): “The first work to venture outside the realm of parametric modeling assumptions appeared in Yang and Zhu (2002).”