Workload-driven learning of mallows mixtures with pairwise preference data. - Julia Stoyanovich; Lovro Ilijasic; Haoyue Ping (WebDB, 2016)

A Database Framework for Probabilistic Preferences. - Batya Kenig; Benny Kimelfeld; Haoyue Ping; Julia Stoyanovich (AMW, 2017)

Querying Probabilistic Preferences in Databases. - Batya Kenig; Benny Kimelfeld; Haoyue Ping; Julia Stoyanovich (PODS, 2017)

DataSynthesizer: Privacy-Preserving Synthetic Datasets. - Haoyue Ping; Julia Stoyanovich; Bill Howe (SSDBM, 2017)

Synthetic Data for Social Good. - Bill Howe; Julia Stoyanovich; Haoyue Ping; Bernease Herman; Matt Gee (CoRR, 2017)

Probabilistic Inference Over Repeated Insertion Models. - Batya Kenig; Lovro Ilijasic; Haoyue Ping; Benny Kimelfeld; Julia Stoyanovich (AAAI, 2018)

A Query Engine for Probabilistic Preferences. - Uzi Cohen; Batya Kenig; Haoyue Ping; Benny Kimelfeld; Julia Stoyanovich (SIGMOD Conference, 2018)

MobilityMirror: Bias-Adjusted Transportation Datasets. - Luke Rodriguez; Babak Salimi; Haoyue Ping; Julia Stoyanovich; Bill Howe (BiDU@VLDB, 2018)

Supporting Hard Queries over Probabilistic Preferences. - Haoyue Ping; Julia Stoyanovich; Benny Kimelfeld (Proc. VLDB Endow., 2020)

Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. - Haoyue Ping; Julia Stoyanovich (Proc. ACM Manag. Data, 2023)