CFML-papers
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Summaries and notes on CounterFactual Machine Learning papers
## 0. 論文概要 Yi Su, Lequn Wang, Michele Santacatterina, Thorsten Joachims. [CAB: Continuous Adaptive Blending Estimator for Policy Evaluation and Learning](https://arxiv.org/abs/1811.02672). arXiv:1811.02672. ## 1. 要約 - Off-Policy Evaluationにおける新たな推定量であるCABを提案 - CABは,...
## 0. 論文概要 Nathan Kallus and Angela Zhou. [Policy Evaluation and Optimization with Continuous Treatments.](https://arxiv.org/abs/1802.06037). Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018, Lanzarote, Spain....
## 0. 論文概要 Yan Zhao, Xiao Fang, and David Simchi-Levi. [Uplift Modeling with Multiple Treatments and General Response Types](https://arxiv.org/pdf/1705.08492.pdf). In proceeding of the SIAM International Conference on Data Mining (SDM17),...
## 0. 論文概要 Shuai Li, Yasin Abbasi-Yadkori, Branislav Kveton, S. Muthukrishnan, Vishwa Vinay, and Zheng Wen. 2018. [Offline Evaluation of Ranking Policies with Click Models](http://delivery.acm.org/10.1145/3230000/3220028/p1685-li.pdf?ip=175.177.5.20&id=3220028&acc=OPENTOC&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E054E54E275136550&__acm__=1548570786_38c0e4201550ecd48c6ffc20a7ca7b14). In KDD ’18: The 24th...
## 0. 論文概要 Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi. 2019. [Top-K Off-Policy Correction for a REINFORCE Recommender System](https://arxiv.org/pdf/1812.02353.pdf). In The Twelfth ACM International...
## 0. 論文概要 Longqi Yang, Yin Cui, Yuan Xuan, Chenyang Wang, Serge Belongie, and Deborah Estrin. 2018. [Unbiased Offline Recommender Evaluation for Missing-Not-At-Random Implicit Feedback.](https://vision.cornell.edu/se3/wp-content/uploads/2018/08/recsys18_unbiased_eval.pdf) In Twelfth ACM Conference on...
## 0. 論文概要 Stephen Bonner and Flavian Vasile. 2017. [Causal Embeddings for Recommendation.](http://delivery.acm.org/10.1145/3250000/3240360/p104-bonner.pdf?ip=131.112.127.95&id=3240360&acc=ACTIVE%20SERVICE&key=D2341B890AD12BFE%2EE857D5F645C75AE5%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&__acm__=1545009137_35415a93c60892508f45f7f0a4a398e1) In The Twelfth ACM Conference on Recommender Systems (RecSys'18), Vol. 1706. ACM, Vancouver, 9. **1 図表は全て本論文からの引用です. **2...
## 0. 論文概要 Thorsten Joachims, Adith Swaminathan, and Tobias Schnabel. 2017. [Unbiased Learning-to-Rank with Biased Feedback.](http://delivery.acm.org/10.1145/3020000/3018699/p781-joachims.pdf?ip=131.112.127.95&id=3018699&acc=CHORUS&key=D2341B890AD12BFE%2EE857D5F645C75AE5%2E4D4702B0C3E38B35%2E6D218144511F3437&__acm__=1544869093_82a47ed86266bcf4f5a64862c6574908) In Proc. of the 10th ACM International Conference on Web Search and Data Mining...
## 0. 論文概要 Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Donald Metzler, Marc Najork. 2018. [Position Bias Estimation for Unbiased Learning to Rank in Personal Search.](https://static.googleusercontent.com/media/research.google.com/ja//pubs/archive/46485.pdf) In WSDM 2018: WSDM 2018:...
## 0. 論文概要 Rolf Jagerman, Ilya Markov, and Maarten de Rijke. [When People Change their Mind: Off-Policy Evaluation in Non-stationary Recommendation Environments](https://staff.fnwi.uva.nl/m.derijke/wp-content/papercite-data/pdf/jagerman-when-2019.pdf). In WSDM 2019: 12th International Conference on Web...