{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T00:00:24Z","timestamp":1778889624111,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,3,8]],"date-time":"2021-03-08T00:00:00Z","timestamp":1615161600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Science Foundation (NSF)","award":["2006844, 2008208, 1934600, 1938167, 195515"],"award-info":[{"award-number":["2006844, 2008208, 1934600, 1938167, 195515"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,3,8]]},"DOI":"10.1145\/3437963.3441818","type":"proceedings-article","created":{"date-parts":[[2021,3,6]],"date-time":"2021-03-06T04:36:17Z","timestamp":1615005377000},"page":"166-174","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":28,"title":["Deconfounding with Networked Observational Data in a Dynamic Environment"],"prefix":"10.1145","author":[{"given":"Jing","family":"Ma","sequence":"first","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}]},{"given":"Ruocheng","family":"Guo","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, AZ, USA"}]},{"given":"Chen","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}]},{"given":"Aidong","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}]},{"given":"Jundong","family":"Li","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,3,8]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. Cochrane Database of Systematic Reviews 4","author":"Anglemyer Andrew","year":"2014","unstructured":"Andrew Anglemyer , Hacsi T Horvath , and Lisa Bero . 2014. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. Cochrane Database of Systematic Reviews 4 ( 2014 ). Andrew Anglemyer, Hacsi T Horvath, and Lisa Bero. 2014. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. Cochrane Database of Systematic Reviews 4 (2014)."},{"key":"e_1_3_2_1_2_1","volume-title":"International Conference on Machine Learning.","author":"Bica Ioana","year":"2020","unstructured":"Ioana Bica , Ahmed Alaa , and Mihaela Van Der Schaar . 2020 . Time series deconfounder: estimating treatment effects over time in the presence of hidden confounders . In International Conference on Machine Learning. Ioana Bica, Ahmed Alaa, and Mihaela Van Der Schaar. 2020. Time series deconfounder: estimating treatment effects over time in the presence of hidden confounders. In International Conference on Machine Learning."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240360"},{"key":"e_1_3_2_1_4_1","volume-title":"Machine Learning","volume":"45","author":"Breiman Leo","year":"2001","unstructured":"Leo Breiman . 2001 . Random forests . Machine Learning , Vol. 45 , 1 (2001). Leo Breiman. 2001. Random forests. Machine Learning, Vol. 45, 1 (2001)."},{"key":"e_1_3_2_1_5_1","volume-title":"Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio.","author":"Cho Kyunghyun","year":"2014","unstructured":"Kyunghyun Cho , Bart Van Merri\u00ebnboer , Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 . Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014). Kyunghyun Cho, Bart Van Merri\u00ebnboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)."},{"key":"e_1_3_2_1_6_1","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"Ganin Yaroslav","year":"2016","unstructured":"Yaroslav Ganin , Evgeniya Ustinova , Hana Ajakan , Pascal Germain , Hugo Larochelle , Francc ois Laviolette , Mario Marchand , and Victor Lempitsky . 2016 . Domain-adversarial training of neural networks . The Journal of Machine Learning Research , Vol. 17 , 1 (2016). Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, Francc ois Laviolette, Mario Marchand, and Victor Lempitsky. 2016. Domain-adversarial training of neural networks. The Journal of Machine Learning Research, Vol. 17, 1 (2016).","journal-title":"The Journal of Machine Learning Research"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397269"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611976236.31"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371816"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/625"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1080\/09243453.2013.806334"},{"key":"e_1_3_2_1_12_1","unstructured":"Ehsan Hajiramezanali Arman Hasanzadeh Krishna Narayanan Nick Duffield Mingyuan Zhou and Xiaoning Qian. 2019. Variational graph recurrent neural networks. In Advances in Neural Information Processing Systems.  Ehsan Hajiramezanali Arman Hasanzadeh Krishna Narayanan Nick Duffield Mingyuan Zhou and Xiaoning Qian. 2019. Variational graph recurrent neural networks. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1198\/jcgs.2010.08162"},{"key":"e_1_3_2_1_14_1","volume-title":"International Conference on Machine Learning.","author":"Johansson Fredrik","year":"2016","unstructured":"Fredrik Johansson , Uri Shalit , and David Sontag . 2016 . Learning representations for counterfactual inference . In International Conference on Machine Learning. Fredrik Johansson, Uri Shalit, and David Sontag. 2016. Learning representations for counterfactual inference. In International Conference on Machine Learning."},{"key":"e_1_3_2_1_15_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling . 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 ( 2016 ). Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/ast066"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132919"},{"key":"e_1_3_2_1_19_1","unstructured":"Christos Louizos Uri Shalit Joris M Mooij David Sontag Richard Zemel and Max Welling. 2017. Causal effect inference with deep latent-variable models. In Advances in Neural Information Processing Systems.  Christos Louizos Uri Shalit Joris M Mooij David Sontag Richard Zemel and Max Welling. 2017. Causal effect inference with deep latent-variable models. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_20_1","volume-title":"Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025","author":"Luong Minh-Thang","year":"2015","unstructured":"Minh-Thang Luong , Hieu Pham , and Christopher D Manning . 2015. Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025 ( 2015 ). Minh-Thang Luong, Hieu Pham, and Christopher D Manning. 2015. Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025 (2015)."},{"key":"e_1_3_2_1_21_1","unstructured":"Terence C Mills and Terence C Mills. 1991. Time series techniques for economists.  Terence C Mills and Terence C Mills. 1991. Time series techniques for economists."},{"key":"e_1_3_2_1_22_1","volume-title":"Roczniki Nauk Rolniczych","volume":"10","author":"Neyman Jersey","year":"1923","unstructured":"Jersey Neyman . 1923 . Sur les applications de la th\u00e9orie des probabilit\u00e9s aux experiences agricoles: Essai des principes . Roczniki Nauk Rolniczych , Vol. 10 (1923). Jersey Neyman. 1923. Sur les applications de la th\u00e9orie des probabilit\u00e9s aux experiences agricoles: Essai des principes. Roczniki Nauk Rolniczych, Vol. 10 (1923)."},{"key":"e_1_3_2_1_23_1","volume-title":"On measurement bias in causal inference. arXiv preprint arXiv:1203.3504","author":"Pearl Judea","year":"2012","unstructured":"Judea Pearl . 2012. On measurement bias in causal inference. arXiv preprint arXiv:1203.3504 ( 2012 ). Judea Pearl. 2012. On measurement bias in causal inference. arXiv preprint arXiv:1203.3504 (2012)."},{"key":"e_1_3_2_1_24_1","volume-title":"Statistics Surveys","volume":"3","author":"Judea","year":"2009","unstructured":"Judea Pearl et al. 2009. Causal inference in statistics: An overview . Statistics Surveys , Vol. 3 ( 2009 ). Judea Pearl et al. 2009. Causal inference in statistics: An overview. Statistics Surveys, Vol. 3 (2009)."},{"key":"e_1_3_2_1_25_1","volume-title":"Genetics","volume":"155","author":"Pritchard Jonathan K","year":"2000","unstructured":"Jonathan K Pritchard , Matthew Stephens , and Peter Donnelly . 2000 . Inference of population structure using multilocus genotype data . Genetics , Vol. 155 , 2 (2000). Jonathan K Pritchard, Matthew Stephens, and Peter Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics, Vol. 155, 2 (2000)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3269267"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/70.1.41"},{"key":"e_1_3_2_1_28_1","volume-title":"Handbook of Statistics","volume":"25","author":"Rubin Donald B","year":"2005","unstructured":"Donald B Rubin . 2005 . Bayesian inference for causal effects . Handbook of Statistics , Vol. 25 (2005). Donald B Rubin. 2005. Bayesian inference for causal effects. Handbook of Statistics, Vol. 25 (2005)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00532240"},{"key":"e_1_3_2_1_30_1","volume-title":"Recommendations as treatments: debiasing learning and evaluation. arXiv preprint arXiv:1602.05352","author":"Schnabel Tobias","year":"2016","unstructured":"Tobias Schnabel , Adith Swaminathan , Ashudeep Singh , Navin Chandak , and Thorsten Joachims . 2016. Recommendations as treatments: debiasing learning and evaluation. arXiv preprint arXiv:1602.05352 ( 2016 ). Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, and Thorsten Joachims. 2016. Recommendations as treatments: debiasing learning and evaluation. arXiv preprint arXiv:1602.05352 (2016)."},{"key":"e_1_3_2_1_31_1","volume-title":"International Conference on Machine Learning.","author":"Shalit Uri","year":"2017","unstructured":"Uri Shalit , Fredrik D Johansson , and David Sontag . 2017 . Estimating individual treatment effect: generalization bounds and algorithms . In International Conference on Machine Learning. Uri Shalit, Fredrik D Johansson, and David Sontag. 2017. Estimating individual treatment effect: generalization bounds and algorithms. In International Conference on Machine Learning."},{"key":"e_1_3_2_1_32_1","volume-title":"AAAI Conference on Artificial Intelligence.","author":"Sun Wei","year":"2015","unstructured":"Wei Sun , Pengyuan Wang , Dawei Yin , Jian Yang , and Yi Chang . 2015 . Causal inference via sparse additive models with application to online advertising . In AAAI Conference on Artificial Intelligence. Wei Sun, Pengyuan Wang, Dawei Yin, Jian Yang, and Yi Chang. 2015. Causal inference via sparse additive models with application to online advertising. In AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_1_33_1","volume-title":"Propensity score methodology in the presence of network entanglement between treatments. arXiv preprint arXiv:1801.07310","author":"Toulis Panos","year":"2018","unstructured":"Panos Toulis , Alexander Volfovsky , and Edoardo M Airoldi . 2018. Propensity score methodology in the presence of network entanglement between treatments. arXiv preprint arXiv:1801.07310 ( 2018 ). Panos Toulis, Alexander Volfovsky, and Edoardo M Airoldi. 2018. Propensity score methodology in the presence of network entanglement between treatments. arXiv preprint arXiv:1801.07310 (2018)."},{"key":"e_1_3_2_1_34_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems.  Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_35_1","volume-title":"Using text embeddings for causal inference. arXiv preprint arXiv:1905.12741","author":"Veitch Victor","year":"2019","unstructured":"Victor Veitch , Dhanya Sridhar , and David M Blei . 2019. Using text embeddings for causal inference. arXiv preprint arXiv:1905.12741 ( 2019 ). Victor Veitch, Dhanya Sridhar, and David M Blei. 2019. Using text embeddings for causal inference. arXiv preprint arXiv:1905.12741 (2019)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1319839"},{"key":"e_1_3_2_1_37_1","article-title":"The blessings of multiple causes","volume":"114","author":"Wang Yixin","year":"2019","unstructured":"Yixin Wang and David M Blei . 2019 . The blessings of multiple causes . J. Amer. Statist. Assoc. , Vol. 114 , 528 (2019). Yixin Wang and David M Blei. 2019. The blessings of multiple causes. J. Amer. Statist. Assoc., Vol. 114, 528 (2019).","journal-title":"J. Amer. Statist. Assoc."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.3354\/cr030079"},{"key":"e_1_3_2_1_39_1","unstructured":"Liuyi Yao Sheng Li Yaliang Li Mengdi Huai Jing Gao and Aidong Zhang. 2018. Representation learning for treatment effect estimation from observational data. In Advances in Neural Information Processing Systems.  Liuyi Yao Sheng Li Yaliang Li Mengdi Huai Jing Gao and Aidong Zhang. 2018. Representation learning for treatment effect estimation from observational data. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/187"}],"event":{"name":"WSDM '21: The Fourteenth ACM International Conference on Web Search and Data Mining","location":"Virtual Event Israel","acronym":"WSDM '21","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 14th ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3437963.3441818","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3437963.3441818","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:36Z","timestamp":1750193256000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3437963.3441818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,8]]},"references-count":40,"alternative-id":["10.1145\/3437963.3441818","10.1145\/3437963"],"URL":"https:\/\/doi.org\/10.1145\/3437963.3441818","relation":{},"subject":[],"published":{"date-parts":[[2021,3,8]]},"assertion":[{"value":"2021-03-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}