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ORCIDJulia Stoyanovich
Person information
- affiliation: New York University, NY, USA
- affiliation (former): Drexel University
- affiliation (former): Columbia University, New York City, USA
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2020 – today
- 2023
[j29]Meike Zehlike
, Ke Yang, Julia Stoyanovich:
Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems. ACM Comput. Surv. 55(6): 117:1-117:41 (2023)- [j28]Meike Zehlike, Ke Yang, Julia Stoyanovich:
Fairness in Ranking, Part I: Score-Based Ranking. ACM Comput. Surv. 55(6): 118:1-118:36 (2023) - [j27]Mona Sloane, Ian Solano-Kamaiko, Jun Yuan, Aritra Dasgupta, Julia Stoyanovich:
Introducing contextual transparency for automated decision systems. Nat. Mac. Intell. 5(3): 187-195 (2023) - [j26]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) - [c64]Andrew Bell, Oded Nov, Julia Stoyanovich:
The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization's Algorithms. CHI Extended Abstracts 2023: 554:1-554:4 - [c63]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [e7]Julia Stoyanovich, Jens Teubner, Nikos Mamoulis, Evaggelia Pitoura, Jan Mühlig, Katja Hose, Sourav S. Bhowmick, Matteo Lissandrini:
Proceedings 26th International Conference on Extending Database Technology, EDBT 2023, Ioannina, Greece, March 28-31, 2023. OpenProceedings.org 2023, ISBN 978-3-89318-088-2 [contents] - [i39]Falaah Arif Khan, Denys Herasymuk, Julia Stoyanovich:
On Fairness and Stability: Is Estimator Variance a Friend or a Foe? CoRR abs/2302.04525 (2023) - [i38]Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Herasymova, Lucas Rosenblatt, Julia Stoyanovich:
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. CoRR abs/2302.06347 (2023) - [i37]Falaah Arif Khan, Julia Stoyanovich:
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction. CoRR abs/2302.08704 (2023) - 2022
- [j25]Armanda Lewis, Julia Stoyanovich:
Teaching Responsible Data Science: Charting New Pedagogical Territory. Int. J. Artif. Intell. Educ. 32(3): 783-807 (2022) - [j24]Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, Sebastian Schelter:
Responsible data management. Commun. ACM 65(6): 64-74 (2022) - [j23]Alene K. Rhea, Kelsey Markey, Lauren D'Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Falaah Arif Khan, Julia Stoyanovich:
An external stability audit framework to test the validity of personality prediction in AI hiring. Data Min. Knowl. Discov. 36(6): 2153-2193 (2022) - [j22]H. V. Jagadish, Julia Stoyanovich, Bill Howe:
The Many Facets of Data Equity. ACM J. Data Inf. Qual. 14(4): 27:1-27:21 (2022) - [j21]Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter:
Data distribution debugging in machine learning pipelines. VLDB J. 31(5): 1103-1126 (2022) - [c62]Alene K. Rhea, Kelsey Markey, Lauren D'Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Julia Stoyanovich:
Resume Format, LinkedIn URLs and Other Unexpected Influences on AI Personality Prediction in Hiring: Results of an Audit. AIES 2022: 572-587 - [c61]Julia Stoyanovich:
Teaching Responsible Data Science. DataEd@SIGMOD 2022: 4-9 - [c60]Falaah Arif Khan, Eleni Manis, Julia Stoyanovich:
Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines. EAAMO 2022: 18:1-18:10 - [c59]Andrew Bell, Ian Solano-Kamaiko, Oded Nov, Julia Stoyanovich:
It's Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy. FAccT 2022: 248-266 - [c58]Marcelo Arenas, Pedro Bahamondes, Amir Aghasadeghi, Julia Stoyanovich:
Temporal Regular Path Queries. ICDE 2022: 2412-2425 - [e6]Julia Stoyanovich, Jens Teubner, Paolo Guagliardo, Milos Nikolic, Andreas Pieris, Jan Mühlig, Fatma Özcan, Sebastian Schelter, H. V. Jagadish, Meihui Zhang:
Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022, Edinburgh, UK, March 29 - April 1, 2022. OpenProceedings.org 2022, ISBN 978-3-89318-086-8 [contents] - [i36]Alene K. Rhea, Kelsey Markey, Lauren D'Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Julia Stoyanovich:
External Stability Auditing to Test the Validity of Personality Prediction in AI Hiring. CoRR abs/2201.09151 (2022) - [i35]Lucas Rosenblatt, Joshua Allen, Julia Stoyanovich:
Spending Privacy Budget Fairly and Wisely. CoRR abs/2204.12903 (2022) - [i34]Amir Pouya Aghasadeghi, Jan Van den Bussche, Julia Stoyanovich:
Temporal graph patterns by timed automata. CoRR abs/2205.14269 (2022) - [i33]Andrew Bell, Oded Nov, Julia Stoyanovich:
Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance. CoRR abs/2207.01482 (2022) - [i32]Falaah Arif Khan, Eleni Manis, Julia Stoyanovich:
Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines. CoRR abs/2207.02912 (2022) - [i31]Lucas Rosenblatt, Anastasia Holovenko, Taras Rumezhak, Andrii Stadnik, Bernease Herman, Julia Stoyanovich, Bill Howe:
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. CoRR abs/2208.12700 (2022) - [i30]Jun Yuan, Julia Stoyanovich, Aritra Dasgupta:
Rankers, Rankees, & Rankings: Peeking into the Pandora's Box from a Socio-Technical Perspective. CoRR abs/2211.02932 (2022) - [i29]Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich:
Counterfactuals for the Future. CoRR abs/2212.03974 (2022) - 2021
- [j20]H. V. Jagadish, Julia Stoyanovich, Bill Howe:
COVID-19 Brings Data Equity Challenges to the Fore. Digit. Gov. Res. Pract. 2(2): 24:1-24:7 (2021) - [j19]Anna Jobin, Kingson Man, Antonio Damasio, Georgios Kaissis, Rickmer Braren, Julia Stoyanovich, Jay J. Van Bavel, Tessa V. West, Brent D. Mittelstadt, Jason Eshraghian, Marta R. Costa-jussà, Asaf Tzachor, Aimun A. B. Jamjoom, Mariarosaria Taddeo, Edoardo Sinibaldi, Yipeng Hu, Miguel A. Luengo-Oroz:
AI reflections in 2020. Nat. Mach. Intell. 3(1): 2-8 (2021) - [j18]Vishal Chakraborty, Theo Delemazure, Benny Kimelfeld, Phokion G. Kolaitis, Kunal Relia, Julia Stoyanovich:
Algorithmic Techniques for Necessary and Possible Winners. Trans. Data Sci. 2(3): 22:1-22:23 (2021) - [c57]Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter:
Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. CIDR 2021 - [c56]Lucius Bynum, Joshua R. Loftus, Julia Stoyanovich:
Disaggregated Interventions to Reduce Inequality. EAAMO 2021: 2:1-2:13 - [c55]H. V. Jagadish, Julia Stoyanovich, Bill Howe:
The Many Facets of Data Equity. EDBT/ICDT Workshops 2021 - [c54]Ke Yang, Joshua R. Loftus, Julia Stoyanovich:
Causal Intersectionality and Fair Ranking. FORC 2021: 7:1-7:20 - [c53]Julia Stoyanovich:
Comparing Apples and Oranges: Fairness and Diversity in Ranking (Invited Talk). ICDT 2021: 2:1-2:1 - [c52]Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter:
MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. SIGMOD Conference 2021: 2736-2739 - [e5]Matthias Boehm, Julia Stoyanovich, Steven Whang:
Proceedings of the Fifth Workshop on Data Management for End-To-End Machine Learning, In conjunction with the 2021 ACM SIGMOD/PODS Conference, DEEM@SIGMOD 2021, Virtual Event, China, 20 June, 2021. ACM 2021, ISBN 978-1-4503-8486-5 [contents] - [i28]Meike Zehlike, Ke Yang, Julia Stoyanovich:
Fairness in Ranking: A Survey. CoRR abs/2103.14000 (2021) - [i27]Haoyue Ping, Julia Stoyanovich:
Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. CoRR abs/2105.00082 (2021) - [i26]Falaah Arif Khan, Eleni Manis, Julia Stoyanovich:
Fairness as Equality of Opportunity: Normative Guidance from Political Philosophy. CoRR abs/2106.08259 (2021) - [i25]Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich:
Impact Remediation: Optimal Interventions to Reduce Inequality. CoRR abs/2107.00593 (2021) - [i24]Marcelo Arenas, Pedro Bahamondes, Julia Stoyanovich:
Temporal Regular Path Queries: Syntax, Semantics, and Complexity. CoRR abs/2107.01241 (2021) - 2020
- [j17]Sebastian Schelter, Julia Stoyanovich:
Taming Technical Bias in Machine Learning Pipelines. IEEE Data Eng. Bull. 43(4): 39-50 (2020) - [j16]Julia Stoyanovich, Jay J. Van Bavel, Tessa V. West:
The imperative of interpretable machines. Nat. Mach. Intell. 2(4): 197-199 (2020) - [j15]Haoyue Ping, Julia Stoyanovich, Benny Kimelfeld:
Supporting Hard Queries over Probabilistic Preferences. Proc. VLDB Endow. 13(7): 1134-1146 (2020) - [j14]Julia Stoyanovich, Bill Howe, H. V. Jagadish:
Responsible Data Management. Proc. VLDB Endow. 13(12): 3474-3488 (2020) - [c51]Amir Aghasadeghi, Vera Zaychik Moffitt, Sebastian Schelter, Julia Stoyanovich:
Zooming Out on an Evolving Graph. EDBT 2020: 25-36 - [c50]Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich:
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. EDBT 2020: 395-398 - [e4]Sebastian Schelter, Steven Whang, Julia Stoyanovich:
Proceedings of the Fourth Workshop on Data Management for End-To-End Machine Learning, In conjunction with the 2020 ACM SIGMOD/PODS Conference, DEEM@SIGMOD 2020, Portland, OR, USA, June 14, 2020. ACM 2020, ISBN 978-1-4503-8023-2 [contents] - [i23]Haoyue Ping, Julia Stoyanovich, Benny Kimelfeld:
Supporting Hard Queries over Probabilistic Preferences. CoRR abs/2003.06984 (2020) - [i22]Vishal Chakraborty, Theo Delemazure, Benny Kimelfeld, Phokion G. Kolaitis, Kunal Relia, Julia Stoyanovich:
Algorithmic Techniques for Necessary and Possible Winners. CoRR abs/2005.06779 (2020) - [i21]Ke Yang, Joshua R. Loftus, Julia Stoyanovich:
Causal intersectionality for fair ranking. CoRR abs/2006.08688 (2020)
2010 – 2019
- 2019
- [j13]Julia Stoyanovich, Bill Howe:
Nutritional Labels for Data and Models. IEEE Data Eng. Bull. 42(3): 13-23 (2019) - [j12]Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich:
Towards Responsible Data-driven Decision Making in Score-Based Systems. IEEE Data Eng. Bull. 42(3): 76-87 (2019) - [j11]Serge Abiteboul, Julia Stoyanovich:
Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation. ACM J. Data Inf. Qual. 11(3): 15:1-15:9 (2019) - [c49]Julia Stoyanovich:
TransFAT: Translating Fairness, Accountably and Transparency into Data Science Practice. PIE@CAiSE 2019 - [c48]Chenkai Sun, Abolfazl Asudeh, H. V. Jagadish, Bill Howe, Julia Stoyanovich:
MithraLabel: Flexible Dataset Nutritional Labels for Responsible Data Science. CIKM 2019: 2893-2896 - [c47]Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich:
Balanced Ranking with Diversity Constraints. IJCAI 2019: 6035-6042 - [c46]H. V. Jagadish, Francesco Bonchi, Tina Eliassi-Rad, Lise Getoor, Krishna P. Gummadi, Julia Stoyanovich:
The Responsibility Challenge for Data. SIGMOD Conference 2019: 412-414 - [c45]Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich, Gautam Das:
Designing Fair Ranking Schemes. SIGMOD Conference 2019: 1259-1276 - [c44]Yifan Guan, Abolfazl Asudeh, Pranav Mayuram, H. V. Jagadish, Julia Stoyanovich, Gerome Miklau, Gautam Das:
MithraRanking: A System for Responsible Ranking Design. SIGMOD Conference 2019: 1913-1916 - [i20]Serge Abiteboul, Julia Stoyanovich:
Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation. CoRR abs/1903.03683 (2019) - [i19]Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich:
Balanced Ranking with Diversity Constraints. CoRR abs/1906.01747 (2019) - [i18]Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich:
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. CoRR abs/1911.12587 (2019) - [i17]Julia Stoyanovich, Armanda Lewis:
Teaching Responsible Data Science: Charting New Pedagogical Territory. CoRR abs/1912.10564 (2019) - 2018
- [j10]Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi:
Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). Dagstuhl Manifestos 7(1): 1-29 (2018) - [j9]Julia Stoyanovich, Bill Howe, H. V. Jagadish, Gerome Miklau:
Panel: A Debate on Data and Algorithmic Ethics. Proc. VLDB Endow. 11(12): 2165-2167 (2018) - [j8]Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, Julia Stoyanovich:
On Obtaining Stable Rankings. Proc. VLDB Endow. 12(3): 237-250 (2018) - [c43]Batya Kenig, Lovro Ilijasic, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich:
Probabilistic Inference Over Repeated Insertion Models. AAAI 2018: 1897-1904 - [c42]Julia Stoyanovich, Ke Yang, H. V. Jagadish:
Online Set Selection with Fairness and Diversity Constraints. EDBT 2018: 241-252 - [c41]Benny Kimelfeld, Phokion G. Kolaitis, Julia Stoyanovich:
Computational Social Choice Meets Databases. IJCAI 2018: 317-323 - [c40]Amir Aghasadeghi, Julia Stoyanovich:
Generating Evolving Property Graphs with Attribute-Aware Preferential Attachment. DBTest@SIGMOD 2018: 7:1-7:6 - [c39]Uzi Cohen, Batya Kenig, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich:
A Query Engine for Probabilistic Preferences. SIGMOD Conference 2018: 1509-1524 - [c38]Julia Stoyanovich, Bill Howe, H. V. Jagadish:
Special Session: A Technical Research Agenda in Data Ethics and Responsible Data Management. SIGMOD Conference 2018: 1635-1636 - [c37]Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau:
A Nutritional Label for Rankings. SIGMOD Conference 2018: 1773-1776 - [c36]Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, Bill Howe:
MobilityMirror: Bias-Adjusted Transportation Datasets. BiDU@VLDB 2018: 18-39 - [c35]Julia Stoyanovich, Matthew Gilbride, Vera Zaychik Moffitt:
Zooming in on NYC Taxi Data with Portal. BiDu-Posters@VLDB 2018 - [i16]Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau:
A Nutritional Label for Rankings. CoRR abs/1804.07890 (2018) - [i15]Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, Julia Stoyanovich:
On Obtaining Stable Rankings. CoRR abs/1804.10990 (2018) - [i14]Benny Kimelfeld, Phokion G. Kolaitis, Julia Stoyanovich:
Computational Social Choice Meets Databases. CoRR abs/1805.04156 (2018) - [i13]Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, Bill Howe:
MobilityMirror: Bias-Adjusted Transportation Datasets. CoRR abs/1808.07151 (2018) - 2017
- [j7]Marina Drosou, H. V. Jagadish, Evaggelia Pitoura, Julia Stoyanovich:
Diversity in Big Data: A Review. Big Data 5(2): 73-84 (2017) - [c34]Batya Kenig, Benny Kimelfeld, Haoyue Ping, Julia Stoyanovich:
A Database Framework for Probabilistic Preferences. AMW 2017 - [c33]Vera Zaychik Moffitt, Julia Stoyanovich:
Temporal graph algebra. DBPL 2017: 10:1-10:12 - [c32]Vera Zaychik Moffitt, Julia Stoyanovich:
Towards sequenced semantics for evolving graphs. EDBT 2017: 446-449 - [c31]Batya Kenig, Benny Kimelfeld, Haoyue Ping, Julia Stoyanovich:
Querying Probabilistic Preferences in Databases. PODS 2017: 21-36 - [c30]Ke Yang, Julia Stoyanovich:
Measuring Fairness in Ranked Outputs. SSDBM 2017: 22:1-22:6 - [c29]Julia Stoyanovich, Bill Howe, Serge Abiteboul, Gerome Miklau, Arnaud Sahuguet, Gerhard Weikum:
Fides: Towards a Platform for Responsible Data Science. SSDBM 2017: 26:1-26:6 - [c28]Haoyue Ping, Julia Stoyanovich, Bill Howe:
DataSynthesizer: Privacy-Preserving Synthetic Datasets. SSDBM 2017: 42:1-42:5 - [e3]Yannis E. Ioannidis, Julia Stoyanovich, Giorgio Orsi:
Proceedings of the Workshops of the EDBT/ICDT 2017 Joint Conference (EDBT/ICDT 2017), Venice, Italy, March 21-24, 2017. CEUR Workshop Proceedings 1810, CEUR-WS.org 2017 [contents] - [i12]Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi:
Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). CoRR abs/1701.09007 (2017) - [i11]Julia Stoyanovich, Matthew Gilbride, Vera Zaychik Moffitt:
Zooming in on NYC taxi data with Portal. CoRR abs/1709.06176 (2017) - [i10]Bill Howe, Julia Stoyanovich, Haoyue Ping, Bernease Herman, Matt Gee:
Synthetic Data for Social Good. CoRR abs/1710.08874 (2017) - [i9]Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich, Gautam Das:
Designing Fair Ranking Schemes. CoRR abs/1712.09752 (2017) - 2016
- [j6]Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi:
Research Directions for Principles of Data Management (Abridged). SIGMOD Rec. 45(4): 5-17 (2016) - [c27]Julia Stoyanovich, Serge Abiteboul, Gerome Miklau:
Data Responsibly: Fairness, Neutrality and Transparency in Data Analysis. EDBT 2016: 718-719 - [c26]Julia Stoyanovich, Lovro Ilijasic, Haoyue Ping:
Workload-driven learning of mallows mixtures with pairwise preference data. WebDB 2016: 8 - [c25]Vera Zaychik Moffitt, Julia Stoyanovich:
Towards a Distributed Infrastructure for Evolving Graph Analytics. WWW (Companion Volume) 2016: 843-848 - [i8]Vera Zaychik Moffitt, Julia Stoyanovich:
Portal: A Query Language for Evolving Graphs. CoRR abs/1602.00773 (2016) - [i7]Ke Yang, Julia Stoyanovich:
Measuring Fairness in Ranked Outputs. CoRR abs/1610.08559 (2016) - [i6]Serge Abiteboul, Gerome Miklau, Julia Stoyanovich, Gerhard Weikum:
Data, Responsibly (Dagstuhl Seminar 16291). Dagstuhl Reports 6(7): 42-71 (2016) - 2015
- [c24]Vera Zaychik Moffitt, Julia Stoyanovich, Serge Abiteboul, Gerome Miklau:
Collaborative Access Control in WebdamLog. SIGMOD Conference 2015: 197-211 - [c23]Serge Abiteboul, Xin Luna Dong, Oren Etzioni, Divesh Srivastava, Gerhard Weikum, Julia Stoyanovich, Fabian M. Suchanek:
The elephant in the room: getting value from Big Data. WebDB 2015: 1-5 - [c22]Julia Stoyanovich, Marie Jacob, Xuemei Gong:
Analyzing Crowd Rankings. WebDB 2015: 41-47 - [e2]Julia Stoyanovich, Fabian M. Suchanek:
Proceedings of the 18th International Workshop on Web and Databases, Melbourne, VIC, Australia, May 31, 2015. ACM 2015, ISBN 978-1-4503-3627-7 [contents] - 2014
- [j5]Marie Jacob, Benny Kimelfeld, Julia Stoyanovich:
A System for Management and Analysis of Preference Data. Proc. VLDB Endow. 7(12): 1255-1258 (2014) - 2013
- [c21]Julia Stoyanovich:
Understanding the Structure of Ranked Data. CIDR 2013 - [c20]Julia Stoyanovich, Sihem Amer-Yahia, Susan B. Davidson, Marie Jacob, Tova Milo:
Understanding Local Structure in Ranked Datasets. CIDR 2013 - [c19]Sidath Gunawardena, Rosina O. Weber, Julia Stoyanovich:
Learning Feature Weights from Positive Cases. ICCBR 2013: 134-148 - [c18]Serge Abiteboul, Émilien Antoine, Gerome Miklau, Julia Stoyanovich, Jules Testard:
Rule-based application development using Webdamlog. SIGMOD Conference 2013: 965-968 - [c17]Susan B. Davidson, Xiaocheng Huang, Julia Stoyanovich, Xiaojie Yuan:
Search and result presentation in scientific workflow repositories. SSDBM 2013: 17:1-17:12 - [c16]Julia Stoyanovich, Paramveer S. Dhillon, Susan B. Davidson, Brian Lyons:
Learning to explore scientific workflow repositories. SSDBM 2013: 31:1-31:4 - [i5]Serge Abiteboul, Émilien Antoine, Julia Stoyanovich:
The Webdamlog System Managing Distributed Knowledge on the Web. CoRR abs/1304.4187 (2013) - [i4]Serge Abiteboul, Émilien Antoine, Gerome Miklau, Julia Stoyanovich, Jules Testard:
Rule-Based Application Development using Webdamlog. CoRR abs/1305.3058 (2013) - [i3]Susan B. Davidson, Xiaocheng Huang, Julia Stoyanovich, Xiaojie Yuan:
Search and Result Presentation in Scientific Workflow Repositories. CoRR abs/1305.4195 (2013) - [i2]Serge Abiteboul, Émilien Antoine, Gerome Miklau, Julia Stoyanovich, Vera Zaychik Moffitt:
Introducing Access Control in Webdamlog. CoRR abs/1307.8269 (2013) - 2012
- [c15]Serge Abiteboul, Émilien Antoine, Julia Stoyanovich:
Viewing the Web as a Distributed Knowledge Base. ICDE 2012: 1-4 - [i1]Yael Amsterdamer, Susan B. Davidson, Daniel Deutch, Tova Milo, Julia Stoyanovich, Val Tannen:
Putting Lipstick on Pig: Enabling Database-style Workflow Provenance. CoRR abs/1201.0231 (2012) - 2011
- [j4]Jie Zheng, Julia Stoyanovich, Elisabetta Manduchi, Junmin Liu, Christian J. Stoeckert Jr.:
AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments. Database J. Biol. Databases Curation 2011 (2011) - [j3]Yael Amsterdamer, Susan B. Davidson, Daniel Deutch, Tova Milo, Julia Stoyanovich, Val Tannen:
Putting Lipstick on Pig: Enabling Database-style Workflow Provenance. Proc. VLDB Endow. 5(4): 346-357 (2011)