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2020 – today
- 2023
[j2]Haoyue Ping
, Julia Stoyanovich:
Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. Proc. ACM Manag. Data 1(1): 22:1-22:25 (2023)- 2021
- [i4]Haoyue Ping, Julia Stoyanovich:
Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. CoRR abs/2105.00082 (2021) - 2020
- [j1]Haoyue Ping, Julia Stoyanovich, Benny Kimelfeld:
Supporting Hard Queries over Probabilistic Preferences. Proc. VLDB Endow. 13(7): 1134-1146 (2020) - [i3]Haoyue Ping, Julia Stoyanovich, Benny Kimelfeld:
Supporting Hard Queries over Probabilistic Preferences. CoRR abs/2003.06984 (2020)
2010 – 2019
- 2018
- [c7]Batya Kenig, Lovro Ilijasic, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich:
Probabilistic Inference Over Repeated Insertion Models. AAAI 2018: 1897-1904 - [c6]Uzi Cohen, Batya Kenig, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich:
A Query Engine for Probabilistic Preferences. SIGMOD Conference 2018: 1509-1524 - [c5]Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, Bill Howe:
MobilityMirror: Bias-Adjusted Transportation Datasets. BiDU@VLDB 2018: 18-39 - [i2]Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, Bill Howe:
MobilityMirror: Bias-Adjusted Transportation Datasets. CoRR abs/1808.07151 (2018) - 2017
- [c4]Batya Kenig, Benny Kimelfeld, Haoyue Ping, Julia Stoyanovich:
A Database Framework for Probabilistic Preferences. AMW 2017 - [c3]Batya Kenig, Benny Kimelfeld, Haoyue Ping, Julia Stoyanovich:
Querying Probabilistic Preferences in Databases. PODS 2017: 21-36 - [c2]Haoyue Ping, Julia Stoyanovich, Bill Howe:
DataSynthesizer: Privacy-Preserving Synthetic Datasets. SSDBM 2017: 42:1-42:5 - [i1]Bill Howe, Julia Stoyanovich, Haoyue Ping, Bernease Herman, Matt Gee:
Synthetic Data for Social Good. CoRR abs/1710.08874 (2017) - 2016
- [c1]Julia Stoyanovich, Lovro Ilijasic, Haoyue Ping:
Workload-driven learning of mallows mixtures with pairwise preference data. WebDB 2016: 8
Coauthor Index
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