Smoothness-Adaptive Contextual Bandits
Published Online:26 Jan 2022https://doi.org/10.1287/opre.2021.2215
References
- (1995) The continuum-armed bandit problem. SIAM J. Control Optim. 70(6):1926–1951.Crossref, Google Scholar
- (2019) MNL-bandit: A dynamic learning approach to assortment selection. Oper. Res. 67(5):1453–1485.Link, Google Scholar
- (2018) Optimal inference in a class of regression models. Econometrica 86(2):655–683.Crossref, Google Scholar
- (2007) Fast learning rates for plug-in classifiers. Ann. Statist. 35(2):608–633.Crossref, Google Scholar
- (2007) Improved rates for the stochastic continuum-armed bandit problem. Bshouty N, Gentile C, eds. Internat. Conf. Comput. Learn. Theory (Springer, Berlin, Heidelberg, Germany), 454–468.Google Scholar
- (2021) Personalized dynamic pricing with machine learning: High dimensional features and heterogeneous elasticity. Management Sci. 67(9):5549–5568.Link, Google Scholar
- (2020) Online decision making with high-dimensional covariates. Oper. Res. 68(1):276–294.Link, Google Scholar
- (2021a) Mostly exploration-free algorithms for contextual bandits. Management Sci. 67(3):1329–1349.Link, Google Scholar
- (2021b) Meta dynamic pricing: Learning across experiments. Management Sci., ePub ahead of print September 9, https://doi.org/10.1287/mnsc.2021.4071.Link, Google Scholar
- (2018) Learning personalized product recommendations with customer disengagement. Preprint, submitted August 29, http://dx.doi.org/10.2139/ssrn.3240970.Google Scholar
- (1973) On some global measures of the deviations of density function estimates. Ann. Statist. 1(6):1071–1095.Crossref, Google Scholar
- (2012) Regret analysis of stochastic and nonstochastic multi-armed bandit problems. Foundations Trends Machine Learn. 5(1):1–122.Crossref, Google Scholar
- (2009a) Pure exploration in multi-armed bandits problems. Gavalda R, Lugosi G, Zeugmann T, Zilles S, eds. Internat. Conf. Algorithmic Learn. Theory (Springer, Berlin, Heidelberg, Germany), 23–37.Google Scholar
- (2009b) Online optimization in x-armed bandits. Bengio Y, Schuurmans D, Lafferty J, Williams C, Culotta A, eds. Advances in Neural Information Processing Systems (Curran Associates, Red Hook, NY), 201–208.Google Scholar
- (2012) Honest adaptive confidence bands and self-similar functions. Electronic J. Statist. 6(2012):1490–1516.Google Scholar
- (2013) Adaptive confidence sets in l2. Probab. Theory Related Fields 156(3-4):889–919.Crossref, Google Scholar
- (2017) Artwork personalization at Netflix. Netflix Tech Blog (December 7), https://netflixtechblog.com/artwork-personalization-c589f074ad76.Google Scholar
- (2020) Osom: A simultaneously optimal algorithm for multi-armed and linear contextual bandits. Chiappa S, Calandra R, eds. Internat. Conf. Artificial Intelligence Statist. (PMLR, Cambridge, MA), 1844–1854.Google Scholar
- (2021) Bayesian sequential learning for clinical trials of multiple correlated medical interventions. Management Sci., ePub ahead of print November 5, https://doi.org/10.1287/mnsc.2021.4137.Google Scholar
- (2011) Contextual bandits with linear payoff functions. Gordon G, Dunson D, Dudík M, eds. Internat. Conf. Artificial Intelligence Statist. (JMLR, Cambridge, MA), 208–214.Google Scholar
- (2020) Feature-based dynamic pricing. Management Sci. 66(11):4921–4943.Link, Google Scholar
- (1994) Ideal spatial adaptation by wavelet shrinkage. Biometrika 81(3):425–455.Crossref, Google Scholar
- (1995) Wavelet shrinkage: Asymptopia? J. Roy. Statist. Soc. B 57(2):301–337.Google Scholar
- (2011) Efficient optimal learning for contextual bandits. Preprint, submitted June 13, https://arxiv.org/abs/1106.2369.Google Scholar
- (2019) Model selection for contextual bandits. Wallach H, Larochelle H, Beygelzimer A, d’Alché-Buc F, Fox E, Garnett R, eds. Advances in Neural Information Processing Systems (Curran Associates, Red Hook, NY), 14741–14752.Google Scholar
- (2010) Confidence bands in density estimation. Ann. Statist. 38(2):1122–1170.Crossref, Google Scholar
- (1997) On spatially adaptive estimation of nonparametric regression. Math. Methods Statist. 6(2):135–170.Google Scholar
- (2013) A linear response bandit problem. Stochastic Systems 3(1):230–261.Link, Google Scholar
- (2019) Adaptive sequential experiments with unknown information arrival processes. Preprint, submitted June 28, https://arxiv.org/abs/1907.00107v1.Google Scholar
- (1992) Effect of bias estimation on coverage accuracy of bootstrap confidence intervals for a probability density. Ann. Statist. 20(2):675–694.Crossref, Google Scholar
- (2019) Smooth contextual bandits: Bridging the parametric and non-differentiable regret regimes. Preprint, submitted September 5, https://arxiv.org/abs/1909.02553v1.Google Scholar
- (2019) Dynamic pricing in high-dimensions. J. Machine Learn. Res. 20(1):315–363.Google Scholar
- (1997) Wavelet estimators: Adapting to unknown smoothness. Math. Methods Statist. 6(1):1–25.Google Scholar
- (2020) Dynamic assortment personalization in high dimensions. Oper. Res. 68(4):1020–1037.Link, Google Scholar
- (2005) Nearly tight bounds for the continuum-armed bandit problem. Weiss Y, Schölkopf B, Platt J, eds. Advances in Neural Information Processing Systems (Curran Associates, Red Hook, NY), 697–704.Google Scholar
- (2008) The epoch-greedy algorithm for multi-armed bandits with side information. Koller D, Schuurmans D, Bengio Y, Bottou L, eds. Advances in Neural Information Processing Systems (Curran Associates, Red Hook, NY), 817–824.Google Scholar
- (1997) Optimal spatial adaptation to inhomogeneous smoothness: An approach based on kernel estimates with variable bandwidth selectors. Ann. Statist. 25(3):929–947.Crossref, Google Scholar
- (1992) Asymptotically minimax adaptive estimation. I. Upper bounds. Optimally adaptive estimates. Theory Probab. Appl. 36(4):682–697.Crossref, Google Scholar
- (2020) Dimension reduction in contextual online learning via nonparametric variable selection. Preprint, submitted September 17, https://arxiv.org/abs/2009.08265.Google Scholar
- (2018) Adaptivity to smoothness in x-armed bandits. Bubeck S, Perchet V, Rigollet P, eds. Conf. Learn. Theory (PMLR, Cambridge, MA), 1463–1492.Google Scholar
- (1997) On nonparametric confidence intervals. Ann. Statist. 25(6):2547–2554.Crossref, Google Scholar
- (2018) Optimal adaptive inference in random design binary regression. Bernoulli 24(1):699–739.Crossref, Google Scholar
- (2016) A sharp adaptive confidence ball for self-similar functions. Stochastic Processes Their Appl. 126(12):3913–3934.Crossref, Google Scholar
- (2013) Confidence sets in sparse regression. Ann. Statist. 41(6):2852–2876.Crossref, Google Scholar
- (2013) The multi-armed bandit problem with covariates. Ann. Statist. 41(2):693–721.Crossref, Google Scholar
- (2000) Adaptive confidence interval for pointwise curve estimation. Ann. Statist. 28(1):298–335.Crossref, Google Scholar
- (2016) Randomized allocation with arm elimination in a bandit problem with covariates. Electronic J. Statist. 10(1):242–270.Crossref, Google Scholar
- (2016) Dynamic pricing with demand covariates. Preprint, submitted April 25, https://arxiv.org/abs/1604.07463.Google Scholar
- (2018) The k-nearest neighbour UCB algorithm for multi-armed bandits with covariates. Preprint, submitted March 1, https://arxiv.org/abs/1803.00316.Google Scholar
- (2010) Nonparametric bandits with covariates. Kalai AT, Mohri M, eds. Conf. Learn. Theory (Omnipress, Madison, WI), 54–66.Google Scholar
- (1952) Some aspects of the sequential design of experiments. Bull. Amer. Math. Soc. 58(5):527–535.Crossref, Google Scholar
- (2017) From ads to interventions: Contextual bandits in mobile health. Rehg J, Murphy S, Kumar S, eds. Mobile Health (Springer, Cham, Switzerland), 495–517.Crossref, Google Scholar
- (1933) On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25(3/4):285–294.Crossref, Google Scholar
- (2005) Bandit problems with side observations. IEEE Trans. Automatic Control 50(3):338–355.Crossref, Google Scholar
- (2019) Multi-modal dynamic pricing. Preprint, submitted November 26, http://dx.doi.org/10.2139/ssrn.3489355.Google Scholar
- (1979) A one-armed bandit problem with a concomitant variable. J. Amer. Statist. Assoc. 74(368):799–806.Crossref, Google Scholar
- (2002) Randomized allocation with nonparametric estimation for a multi-armed bandit problem with covariates. Ann. Statist. 30(1):100–121.Crossref, Google Scholar
- (2019) How do tumor cytogenetics inform cancer treatments? Dynamic risk stratification and precision medicine using multi-armed bandits. Preprint, submitted July 12, http://dx.doi.org/10.2139/ssrn.3405082.Google Scholar

