{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T01:58:52Z","timestamp":1773021532848,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":12,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,14]]},"DOI":"10.1145\/3447548.3470792","type":"proceedings-article","created":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T18:33:08Z","timestamp":1628879588000},"page":"4072-4073","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Causal Inference and Machine Learning in Practice with EconML and CausalML"],"prefix":"10.1145","author":[{"given":"Vasilis","family":"Syrgkanis","sequence":"first","affiliation":[{"name":"Microsoft Research, Cambridge, MA, USA"}]},{"given":"Greg","family":"Lewis","sequence":"additional","affiliation":[{"name":"Microsoft Research, Cambridge, MA, USA"}]},{"given":"Miruna","family":"Oprescu","sequence":"additional","affiliation":[{"name":"Microsoft Research, Cambridge, MA, USA"}]},{"given":"Maggie","family":"Hei","sequence":"additional","affiliation":[{"name":"Microsoft Research, Cambridge, MA, USA"}]},{"given":"Keith","family":"Battocchi","sequence":"additional","affiliation":[{"name":"Microsoft Research, Cambridge, MA, USA"}]},{"given":"Eleanor","family":"Dillon","sequence":"additional","affiliation":[{"name":"Microsoft Research, Cambridge, MA, USA"}]},{"given":"Jing","family":"Pan","sequence":"additional","affiliation":[{"name":"Uber Technologies, San Francisco, CA, USA"}]},{"given":"Yifeng","family":"Wu","sequence":"additional","affiliation":[{"name":"Uber Technologies, San Francisco, CA, USA"}]},{"given":"Paul","family":"Lo","sequence":"additional","affiliation":[{"name":"Uber Technologies, San Francisco, CA, USA"}]},{"given":"Huigang","family":"Chen","sequence":"additional","affiliation":[{"name":"Facebook, Menlo Park, CA, USA"}]},{"given":"Totte","family":"Harinen","sequence":"additional","affiliation":[{"name":"Toyota Research Institute, Los Altos, CA, USA"}]},{"given":"Jeong-Yoon","family":"Lee","sequence":"additional","affiliation":[{"name":"Netflix Research, Los Gatos, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Causalml: Python package for causal machine learning. arXiv preprint arXiv:2002.11631","author":"Chen Huigang","year":"2020","unstructured":"Huigang Chen , Totte Harinen , Jeong-Yoon Lee , Mike Yung , and Zhenyu Zhao . 2020 . Causalml: Python package for causal machine learning. arXiv preprint arXiv:2002.11631 (2020). Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Mike Yung, and Zhenyu Zhao. 2020. Causalml: Python package for causal machine learning. arXiv preprint arXiv:2002.11631 (2020)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1257\/aer.p20171038"},{"key":"e_1_3_2_1_3_1","unstructured":"Susan Gruber and Mark J Van Der Laan. 2009. Targeted maximum likelihood estimation: A gentle introduction. (2009).  Susan Gruber and Mark J Van Der Laan. 2009. Targeted maximum likelihood estimation: A gentle introduction. (2009)."},{"key":"e_1_3_2_1_4_1","volume-title":"International Conference on Machine Learning. PMLR, 1414--1423","author":"Hartford Jason","year":"2017","unstructured":"Jason Hartford , Greg Lewis , Kevin Leyton-Brown , and Matt Taddy . 2017 . Deep IV: A flexible approach for counterfactual prediction . In International Conference on Machine Learning. PMLR, 1414--1423 . Jason Hartford, Greg Lewis, Kevin Leyton-Brown, and Matt Taddy. 2017. Deep IV: A flexible approach for counterfactual prediction. In International Conference on Machine Learning. PMLR, 1414--1423."},{"key":"e_1_3_2_1_5_1","volume-title":"Optimal doubly robust estimation of heterogeneous causal effects. arXiv preprint arXiv:2004.14497","author":"Kennedy Edward H","year":"2020","unstructured":"Edward H Kennedy . 2020. Optimal doubly robust estimation of heterogeneous causal effects. arXiv preprint arXiv:2004.14497 ( 2020 ). Edward H Kennedy. 2020. Optimal doubly robust estimation of heterogeneous causal effects. arXiv preprint arXiv:2004.14497 (2020)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1804597116"},{"key":"e_1_3_2_1_7_1","volume-title":"arXiv preprint arXiv:2002.07285","author":"Lewis Greg","year":"2020","unstructured":"Greg Lewis and Vasilis Syrgkanis . 2020. Double\/ Debiased Machine Learning for Dynamic Treatment Effects . arXiv preprint arXiv:2002.07285 ( 2020 ). Greg Lewis and Vasilis Syrgkanis. 2020. Double\/Debiased Machine Learning for Dynamic Treatment Effects. arXiv preprint arXiv:2002.07285 (2020)."},{"key":"e_1_3_2_1_8_1","volume-title":"Causal effect inference with deep latent-variable models. arXiv preprint arXiv:1705.08821","author":"Louizos Christos","year":"2017","unstructured":"Christos Louizos , Uri Shalit , Joris Mooij , David Sontag , Richard Zemel , and Max Welling . 2017. Causal effect inference with deep latent-variable models. arXiv preprint arXiv:1705.08821 ( 2017 ). Christos Louizos, Uri Shalit, Joris Mooij, David Sontag, Richard Zemel, and Max Welling. 2017. Causal effect inference with deep latent-variable models. arXiv preprint arXiv:1705.08821 (2017)."},{"key":"e_1_3_2_1_9_1","unstructured":"Microsoft Research. 2019. EconML: A Python Package for ML-Based Heterogeneous Treatment Effects Estimation . https:\/\/github.com\/microsoft\/EconML. Version 0.x.  Microsoft Research. 2019. EconML: A Python Package for ML-Based Heterogeneous Treatment Effects Estimation . https:\/\/github.com\/microsoft\/EconML. Version 0.x."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-011-0434-0"},{"key":"e_1_3_2_1_11_1","volume-title":"DragonNet: a robust mobile internet service system for long-distance trains","author":"Tso Fung Po","year":"2013","unstructured":"Fung Po Tso , Lin Cui , Lizhuo Zhang , Weijia Jia , Di Yao , Jin Teng , and Dong Xuan . 2013. DragonNet: a robust mobile internet service system for long-distance trains . IEEE transactions on mobile computing , Vol. 12 , 11 ( 2013 ), 2206--2218. Fung Po Tso, Lin Cui, Lizhuo Zhang, Weijia Jia, Di Yao, Jin Teng, and Dong Xuan. 2013. DragonNet: a robust mobile internet service system for long-distance trains. IEEE transactions on mobile computing , Vol. 12, 11 (2013), 2206--2218."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1319839"}],"event":{"name":"KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event Singapore","acronym":"KDD '21","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3470792","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447548.3470792","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:31Z","timestamp":1750191511000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3470792"}},"subtitle":["Industrial Use Cases at Microsoft, TripAdvisor, Uber"],"short-title":[],"issued":{"date-parts":[[2021,8,14]]},"references-count":12,"alternative-id":["10.1145\/3447548.3470792","10.1145\/3447548"],"URL":"https:\/\/doi.org\/10.1145\/3447548.3470792","relation":{},"subject":[],"published":{"date-parts":[[2021,8,14]]},"assertion":[{"value":"2021-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}