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Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference., , , , , , , , и . AAAI, стр. 22331-22340. AAAI Press, (2024)2022 ACM PODS Alberto O. Mendelzon Test-of-Time Award., , и . PODS, стр. 103-104. ACM, (2022)Characterizing and Verifying Queries Via CINSGEN., , , , и . SIGMOD Conference Companion, стр. 143-146. ACM, (2023)Computing Local Sensitivities of Counting Queries with Joins., , , и . SIGMOD Conference, стр. 479-494. ACM, (2020)Causal Relational Learning., , , , , и . SIGMOD Conference, стр. 241-256. ACM, (2020)Hiding Data and Structure in Workflow Provenance., , и . DNIS, том 7108 из Lecture Notes in Computer Science, стр. 41-48. Springer, (2011)Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases., , , и . UAI, AUAI Press, (2013)Circuits for Datalog Provenance., , , и . ICDT, стр. 201-212. OpenProceedings.org, (2014)How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk)., , , , , , и . ICDT, том 290 из LIPIcs, стр. 2:1-2:9. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2024)Counting of Query Expressions: Limitations of Propositional Methods., , , и . ICDT, стр. 177-188. OpenProceedings.org, (2014)