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[1] Adel Javanmard,et al. Online Debiasing for Adaptively Collected High-dimensional Data , 2019, ArXiv.
[2] D.G. Dudley,et al. Dynamic system identification experiment design and data analysis , 1979, Proceedings of the IEEE.
[3] Kelly W. Zhang,et al. Inference for Batched Bandits , 2020, NeurIPS.
[4] Stefan Wager,et al. Confidence intervals for policy evaluation in adaptive experiments , 2021, Proceedings of the National Academy of Sciences.
[5] H. Robbins,et al. Strong consistency of least squares estimates in multiple regression , 1978 .
[6] Martin J. Wainwright,et al. High-Dimensional Statistics , 2019 .
[7] Gábor Lugosi,et al. Concentration Inequalities - A Nonasymptotic Theory of Independence , 2013, Concentration Inequalities.
[8] Tao Qin,et al. Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising , 2013, NIPS.
[9] Jack Bowden,et al. Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges. , 2015, Statistical science : a review journal of the Institute of Mathematical Statistics.
[10] Csaba Szepesvári,et al. Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems , 2011, ArXiv.
[11] I. A. Ibragimov,et al. ASYMPTOTIC NORMALITY FOR SUMS OF DEPENDENT RANDOM VARIABLES , 2005 .
[12] T. Lai,et al. Least Squares Estimates in Stochastic Regression Models with Applications to Identification and Control of Dynamic Systems , 1982 .
[13] Tze Leung Lai,et al. Asymptotic Properties of Nonlinear Least Squares Estimates in Stochastic Regression Models , 1994 .
[14] W. Fuller,et al. Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .
[15] P. Young,et al. Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.
[16] Alessandro Rinaldo,et al. On the bias, risk and consistency of sample means in multi-armed bandits , 2019, SIAM J. Math. Data Sci..
[17] Matthew Malloy,et al. lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits , 2013, COLT.
[18] Jasjeet S. Sekhon,et al. Time-uniform, nonparametric, nonasymptotic confidence sequences , 2020, The Annals of Statistics.
[19] Nicolò Cesa-Bianchi,et al. Gambling in a rigged casino: The adversarial multi-armed bandit problem , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.
[20] Doreen Meier,et al. Introduction To Stochastic Control Theory , 2016 .
[21] Wouter M. Koolen,et al. Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals , 2018, J. Mach. Learn. Res..
[22] Vianney Perchet,et al. Online A-Optimal Design and Active Linear Regression , 2021, ICML.
[23] Diane M. Griffiths,et al. THE REGENTS OF THE UNIVERSITY OF CALIFORNIA , 2007 .
[24] Susan A. Murphy,et al. Statistical Inference with M-Estimators on Adaptively Collected Data , 2021, NeurIPS.
[25] John S. White. THE LIMITING DISTRIBUTION OF THE SERIAL CORRELATION COEFFICIENT IN THE EXPLOSIVE CASE , 1958 .
[26] Xinkun Nie,et al. Why adaptively collected data have negative bias and how to correct for it , 2017, AISTATS.
[27] H. Robbins,et al. Adaptive Design and Stochastic Approximation , 1979 .
[28] Csaba Szepesvari,et al. Bandit Algorithms , 2020 .
[29] W. R. Thompson. ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES , 1933 .
[30] Alessandro Rinaldo,et al. Are sample means in multi-armed bandits positively or negatively biased? , 2019, NeurIPS.
[31] Vasilis Syrgkanis,et al. Accurate Inference for Adaptive Linear Models , 2017, ICML.
[32] T. Tony Cai,et al. Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity , 2015, 1506.05539.