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[1] S. Eguchi,et al. Importance Sampling Via the Estimated Sampler , 2007 .
[2] E. Ionides. Truncated Importance Sampling , 2008 .
[3] Yishay Mansour,et al. Learning Bounds for Importance Weighting , 2010, NIPS.
[4] Wei Chu,et al. A contextual-bandit approach to personalized news article recommendation , 2010, WWW '10.
[5] T. Hesterberg,et al. Weighted Average Importance Sampling and Defensive Mixture Distributions , 1995 .
[6] Andrew McCallum,et al. An Introduction to Conditional Random Fields , 2010, Found. Trends Mach. Learn..
[7] Lihong Li,et al. Counterfactual Estimation and Optimization of Click Metrics for Search Engines , 2014, ArXiv.
[8] John Langford,et al. Doubly Robust Policy Evaluation and Optimization , 2014, ArXiv.
[9] B. Delyon,et al. Integral approximation by kernel smoothing , 2014, 1409.0733.
[10] Thorsten Joachims,et al. The Self-Normalized Estimator for Counterfactual Learning , 2015, NIPS.
[11] M. de Rijke,et al. Large-scale Validation of Counterfactual Learning Methods: A Test-Bed , 2016, ArXiv.
[12] Lihong Li,et al. Toward Minimax Off-policy Value Estimation , 2015, AISTATS.
[13] Joaquin Quiñonero Candela,et al. Counterfactual reasoning and learning systems: the example of computational advertising , 2013, J. Mach. Learn. Res..
[14] Thorsten Joachims,et al. Counterfactual Risk Minimization: Learning from Logged Bandit Feedback , 2015, ICML.
[15] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[16] Wei Chu,et al. Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms , 2010, WSDM '11.
[17] Lihong Li,et al. Learning from Logged Implicit Exploration Data , 2010, NIPS.
[18] Jorge Nocedal,et al. On the limited memory BFGS method for large scale optimization , 1989, Math. Program..