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ORCIDJennifer Wortman Vaughan
Jennifer Wortman
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- affiliation: University of California, Los Angeles, USA
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2020 – today
- 2024
[j33]Rupert Freeman
, Jens Witkowski, Jennifer Wortman Vaughan, David M. Pennock:
An Equivalence Between Fair Division and Wagering Mechanisms. Manag. Sci. 70(10): 6704-6723 (2024)- [j32]Michael A. Madaio, Jingya Chen, Hanna M. Wallach, Jennifer Wortman Vaughan:
Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist. Proc. ACM Hum. Comput. Interact. 8(CSCW1): 1-20 (2024) - [j31]Nina Grgic-Hlaca, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan:
(De)Noise: Moderating the Inconsistency Between Human Decision-Makers. Proc. ACM Hum. Comput. Interact. 8(CSCW2): 1-38 (2024) - [c59]Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan:
"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust. FAccT 2024: 822-835 - [i50]K. J. Kevin Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy X. Zhang, David W. McDonald:
Canvil: Designerly Adaptation for LLM-Powered User Experiences. CoRR abs/2401.09051 (2024) - [i49]Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan:
"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust. CoRR abs/2405.00623 (2024) - [i48]Nina Grgic-Hlaca, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan:
(De)Noise: Moderating the Inconsistency Between Human Decision-Makers. CoRR abs/2407.11225 (2024) - [i47]Wesley Hanwen Deng, Solon Barocas, Jennifer Wortman Vaughan:
Supporting Industry Computing Researchers in Assessing, Articulating, and Addressing the Potential Negative Societal Impact of Their Work. CoRR abs/2408.01057 (2024) - [i46]Hanna M. Wallach, Meera A. Desai, Nicholas Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alexandra Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs:
Evaluating Generative AI Systems is a Social Science Measurement Challenge. CoRR abs/2411.10939 (2024) - [i45]P. Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alexandra Chouldechova, Hanna M. Wallach:
Dimensions of Generative AI Evaluation Design. CoRR abs/2411.12709 (2024) - [i44]A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark Lemley, danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, Katherine Lee:
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. CoRR abs/2412.06966 (2024) - [i43]Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi, Eric Horvitz, Adam Fourney, Hussein Mozannar, Victor Dibia, Daniel S. Weld:
Challenges in Human-Agent Communication. CoRR abs/2412.10380 (2024) - 2023
- [j30]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. Manag. Sci. 69(3): 1354-1374 (2023) - [j29]Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal:
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations. Proc. ACM Hum. Comput. Interact. 7(CSCW2): 1-32 (2023) - [j28]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits. SIAM J. Comput. 52(2): 487-524 (2023) - [c58]Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan:
Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience. CHI 2023: 9:1-9:21 - [c57]Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau:
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse. CHI 2023: 835:1-835:20 - [i42]Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal:
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations. CoRR abs/2301.07255 (2023) - [i41]Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan:
Generation Probabilities Are Not Enough: Exploring the Effectiveness of Uncertainty Highlighting in AI-Powered Code Completions. CoRR abs/2302.07248 (2023) - [i40]Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan:
Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience. CoRR abs/2302.10395 (2023) - [i39]Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau:
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse. CoRR abs/2302.14165 (2023) - [i38]Q. Vera Liao, Jennifer Wortman Vaughan:
AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap. CoRR abs/2306.01941 (2023) - [i37]Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment. CoRR abs/2306.03262 (2023) - [i36]Anthony Cintron Roman, Jennifer Wortman Vaughan, Valerie See, Steph Ballard, Nicolas Schifano, Jehu Torres Vega, Caleb Robinson, Juan M. Lavista Ferres:
Open Datasheets: Machine-readable Documentation for Open Datasets and Responsible AI Assessments. CoRR abs/2312.06153 (2023) - 2022
- [j27]Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach:
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. Proc. ACM Hum. Comput. Interact. 6(CSCW1): 52:1-52:26 (2022) - [j26]Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan:
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. Proc. ACM Hum. Comput. Interact. 6(CSCW2): 1-29 (2022) - [c56]Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan:
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. FAccT 2022: 587-597 - [c55]Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana:
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. KDD 2022: 4132-4142 - [i35]Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan:
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. CoRR abs/2205.08363 (2022) - [i34]Amy Heger, Elizabeth B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan:
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. CoRR abs/2206.02923 (2022) - [i33]Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana:
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. CoRR abs/2206.15465 (2022) - [i32]Neha Hulkund, Nicolò Fusi, Jennifer Wortman Vaughan, David Alvarez-Melis:
Interpretable Distribution Shift Detection using Optimal Transport. CoRR abs/2208.02896 (2022) - [i31]Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah:
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? CoRR abs/2211.12966 (2022) - 2021
- [j25]Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L. Gray, Brent J. Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach, Marion Zepf:
Responsible computing during COVID-19 and beyond. Commun. ACM 64(7): 30-32 (2021) - [j24]Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford:
Datasheets for datasets. Commun. ACM 64(12): 86-92 (2021) - [j23]Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna M. Wallach, Jennifer Wortman Vaughan:
Summarize with Caution: Comparing Global Feature Attributions. IEEE Data Eng. Bull. 44(4): 14-27 (2021) - [j22]Rupert Freeman, David M. Pennock, Dominik Peters, Jennifer Wortman Vaughan:
Truthful aggregation of budget proposals. J. Econ. Theory 193: 105234 (2021) - [c54]Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach:
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. AIES 2021: 368-378 - [c53]Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach:
Manipulating and Measuring Model Interpretability. CHI 2021: 237:1-237:52 - [c52]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP 2021: 35-47 - [c51]Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. DaSH@KDD 2021 - [e2]Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. 2021 [contents] - [i30]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. CoRR abs/2101.01816 (2021) - [i29]Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach:
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. CoRR abs/2103.06076 (2021) - [i28]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR abs/2104.13299 (2021) - [i27]Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana:
GAM Changer: Editing Generalized Additive Models with Interactive Visualization. CoRR abs/2112.03245 (2021) - [i26]Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach:
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. CoRR abs/2112.05675 (2021) - 2020
- [j21]Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan:
Oracle-efficient Online Learning and Auction Design. J. ACM 67(5): 26:1-26:57 (2020) - [j20]Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris:
Toward fairness in AI for people with disabilities SBG@a research roadmap. ACM SIGACCESS Access. Comput. 125: 2 (2020) - [j19]Rachel Cummings, David M. Pennock, Jennifer Wortman Vaughan:
The Possibilities and Limitations of Private Prediction Markets. ACM Trans. Economics and Comput. 8(3): 15:1-15:24 (2020) - [c50]Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. CHI 2020: 1-14 - [c49]Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach:
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. CHI 2020: 1-14 - [c48]Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan:
No-Regret and Incentive-Compatible Online Learning. ICML 2020: 3270-3279 - [i25]Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan:
No-Regret and Incentive-Compatible Online Learning. CoRR abs/2002.08837 (2020) - [i24]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
Greedy Algorithm almost Dominates in Smoothed Contextual Bandits. CoRR abs/2005.10624 (2020) - [i23]Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan:
Mathematical Foundations for Social Computing. CoRR abs/2007.03661 (2020)
2010 – 2019
- 2019
- [c47]Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan:
Group Fairness for the Allocation of Indivisible Goods. AAAI 2019: 1853-1860 - [c46]Rupert Freeman, David M. Pennock, Jennifer Wortman Vaughan:
An Equivalence between Wagering and Fair-Division Mechanisms. AAAI 2019: 1957-1964 - [c45]Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach:
Understanding the Effect of Accuracy on Trust in Machine Learning Models. CHI 2019: 279 - [c44]Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach:
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI 2019: 600 - [c43]Rupert Freeman, David M. Pennock, Dominik Peters, Jennifer Wortman Vaughan:
Truthful Aggregation of Budget Proposals. EC 2019: 751-752 - [c42]Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan:
The Disparate Effects of Strategic Manipulation. FAT 2019: 259-268 - [c41]Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz:
Using Search Queries to Understand Health Information Needs in Africa. ICWSM 2019: 3-14 - [e1]Edith Law, Jennifer Wortman Vaughan:
Proceedings of the Seventh AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2019, Stevenson, WA, USA, October 28-30, 2019. AAAI Press 2019, ISBN 978-1-57735-820-6 [contents] - [i22]Rupert Freeman, David M. Pennock, Dominik Peters, Jennifer Wortman Vaughan:
Truthful Aggregation of Budget Proposals. CoRR abs/1905.00457 (2019) - [i21]Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris:
Toward Fairness in AI for People with Disabilities: A Research Roadmap. CoRR abs/1907.02227 (2019) - [i20]David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach:
Weight of Evidence as a Basis for Human-Oriented Explanations. CoRR abs/1910.13503 (2019) - 2018
- [j18]Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan:
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets. ACM Trans. Economics and Comput. 6(3-4): 15:1-15:26 (2018) - [c40]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. AAAI 2018: 1282-1289 - [c39]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
The Externalities of Exploration and How Data Diversity Helps Exploitation. COLT 2018: 1724-1738 - [i19]Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach:
Manipulating and Measuring Model Interpretability. CoRR abs/1802.07810 (2018) - [i18]Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford:
Datasheets for Datasets. CoRR abs/1803.09010 (2018) - [i17]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
The Externalities of Exploration and How Data Diversity Helps Exploitation. CoRR abs/1806.00543 (2018) - [i16]Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz:
Using Search Queries to Understand Health Information Needs in Africa. CoRR abs/1806.05740 (2018) - [i15]Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan:
The Disparate Effects of Strategic Manipulation. CoRR abs/1808.08646 (2018) - [i14]Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach:
Improving fairness in machine learning systems: What do industry practitioners need? CoRR abs/1812.05239 (2018) - 2017
- [j17]Jennifer Wortman Vaughan:
Incentives and the crowd. XRDS 24(1): 42-46 (2017) - [j16]Jennifer Wortman Vaughan:
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research. J. Mach. Learn. Res. 18: 193:1-193:46 (2017) - [c38]Jennifer Wortman Vaughan:
Tutorial: Making Better Use of the Crowd. ACL (Tutorial Abstracts) 2017: 17-18 - [c37]Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan:
Oracle-Efficient Online Learning and Auction Design. FOCS 2017: 528-539 - [c36]Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan:
A Decomposition of Forecast Error in Prediction Markets. NIPS 2017: 4371-4380 - [c35]Rupert Freeman, David M. Pennock, Jennifer Wortman Vaughan:
The Double Clinching Auction for Wagering. EC 2017: 43-60 - [i13]Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan:
A Decomposition of Forecast Error in Prediction Markets. CoRR abs/1702.07810 (2017) - 2016
- [j15]Yiling Chen, Arpita Ghosh, Michael J. Kearns, Tim Roughgarden, Jennifer Wortman Vaughan:
Mathematical foundations for social computing. Commun. ACM 59(12): 102-108 (2016) - [j14]Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems. J. Artif. Intell. Res. 55: 317-359 (2016) - [c34]Rachel Cummings, David M. Pennock, Jennifer Wortman Vaughan:
The Possibilities and Limitations of Private Prediction Markets. EC 2016: 143-160 - [c33]David M. Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan:
Bounded Rationality in Wagering Mechanisms. UAI 2016 - [c32]Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan:
The Communication Network Within the Crowd. WWW 2016: 1293-1303 - [i12]Rachel Cummings, David M. Pennock, Jennifer Wortman Vaughan:
The Possibilities and Limitations of Private Prediction Markets. CoRR abs/1602.07362 (2016) - [i11]Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan:
Oracle-Efficient Learning and Auction Design. CoRR abs/1611.01688 (2016) - 2015
- [j13]Nicolas S. Lambert, John Langford, Jennifer Wortman Vaughan, Yiling Chen, Daniel M. Reeves, Yoav Shoham, David M. Pennock:
An axiomatic characterization of wagering mechanisms. J. Econ. Theory 156: 389-416 (2015) - [j12]Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan:
Incentivizing high quality crowdwork. SIGecom Exch. 14(2): 26-34 (2015) - [c31]Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan:
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets. EC 2015: 583-600 - [c30]Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan:
Incentivizing High Quality Crowdwork. WWW 2015: 419-429 - [i10]Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan:
Incentivizing High Quality Crowdwork. CoRR abs/1503.05897 (2015) - 2014
- [j11]Winter A. Mason, Jennifer Wortman Vaughan, Hanna M. Wallach:
Computational social science and social computing. Mach. Learn. 95(3): 257-260 (2014) - [c29]Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Adaptive contract design for crowdsourcing markets: bandit algorithms for repeated principal-agent problems. EC 2014: 359-376 - [c28]Yiling Chen, Nikhil R. Devanur, David M. Pennock, Jennifer Wortman Vaughan:
Removing arbitrage from wagering mechanisms. EC 2014: 377-394 - [c27]Jacob D. Abernethy, Rafael M. Frongillo, Xiaolong Li, Jennifer Wortman Vaughan:
A general volume-parameterized market making framework. EC 2014: 413-430 - [c26]Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan:
Market Making with Decreasing Utility for Information. UAI 2014: 152-161 - [i9]Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems. CoRR abs/1405.2875 (2014) - [i8]Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan:
Market Making with Decreasing Utility for Information. CoRR abs/1407.8161 (2014) - 2013
- [j10]Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Online decision making in crowdsourcing markets: theoretical challenges. SIGecom Exch. 12(2): 4-23 (2013) - [j9]Jacob D. Abernethy, Yiling Chen, Jennifer Wortman Vaughan:
Efficient Market Making via Convex Optimization, and a Connection to Online Learning. ACM Trans. Economics and Comput. 1(2): 12:1-12:39 (2013) - [c25]Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan:
Adaptive Task Assignment for Crowdsourced Classification. ICML (1) 2013: 534-542 - [c24]Xiaolong Li, Jennifer Wortman Vaughan:
An axiomatic characterization of adaptive-liquidity market makers. EC 2013: 657-674 - [c23]Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan:
Cost function market makers for measurable spaces. EC 2013: 785-802 - [i7]Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges (Position Paper). CoRR abs/1308.1746 (2013) - 2012
- [c22]Chien-Ju Ho, Jennifer Wortman Vaughan:
Online Task Assignment in Crowdsourcing Markets. AAAI 2012: 45-51 - [c21]Chien-Ju Ho, Yu Zhang, Jennifer Wortman Vaughan, Mihaela van der Schaar:
Towards Social Norm Design for Crowdsourcing Markets. HCOMP@AAAI 2012 - [c20]Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan:
Designing Informative Securities. UAI 2012: 185-195 - [i6]Kuzman Ganchev, Michael J. Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan:
Censored Exploration and the Dark Pool Problem. CoRR abs/1205.2646 (2012) - [i5]Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan:
Designing Informative Securities. CoRR abs/1210.4837 (2012) - 2011
- [c19]Jacob D. Abernethy, Yiling Chen, Jennifer Wortman Vaughan:
An optimization-based framework for automated market-making. EC 2011: 297-306 - 2010
- [j8]John Langford, Lihong Li, Yevgeniy Vorobeychik, Jennifer Wortman:
Maintaining Equilibria During Exploration in Sponsored Search Auctions. Algorithmica 58(4): 990-1021 (2010) - [j7]Kuzman Ganchev, Yuriy Nevmyvaka, Michael J. Kearns, Jennifer Wortman Vaughan:
Censored exploration and the dark pool problem. Commun. ACM 53(5): 99-107 (2010) - [j6]Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan:
A theory of learning from different domains. Mach. Learn. 79(1-2): 151-175 (2010) - [j5]Maria-Florina Balcan, Steve Hanneke, Jennifer Wortman Vaughan:
The true sample complexity of active learning. Mach. Learn. 80(2-3): 111-139 (2010) - [j4]Yiling Chen, Jennifer Wortman Vaughan:
Connections between markets and learning. SIGecom Exch. 9(1): 6 (2010) - [c18]Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan:
Evolution with Drifting Targets. COLT 2010: 155-167 - [c17]Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jennifer Wortman Vaughan:
Regret Minimization With Concept Drift. COLT 2010: 168-180 - [c16]Yiling Chen, Jennifer Wortman Vaughan:
A new understanding of prediction markets via no-regret learning. EC 2010: 189-198 - [i4]Yiling Chen, Jennifer Wortman Vaughan:
A New Understanding of Prediction Markets Via No-Regret Learning. CoRR abs/1003.0034 (2010) - [i3]Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan:
Evolution with Drifting Targets. CoRR abs/1005.3566 (2010) - [i2]Jacob D. Abernethy, Yiling Chen, Jennifer Wortman Vaughan:
An Optimization-Based Framework for Automated Market-Making. CoRR abs/1011.1941 (2010)
2000 – 2009
- 2009
- [j3]Michael J. Kearns, J. Stephen Judd, Jinsong Tan, Jennifer Wortman:
Behavioral experiments on biased voting in networks. Proc. Natl. Acad. Sci. USA 106(5): 1347-1352 (2009) - [c15]Kuzman Ganchev, Michael J. Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan:
Censored Exploration and the Dark Pool Problem. UAI 2009: 185-194 - 2008
- [j2]Koby Crammer, Michael J. Kearns, Jennifer Wortman:
Learning from Multiple Sources. J. Mach. Learn. Res. 9: 1757-1774 (2008) - [j1]Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman:
Regret to the best vs. regret to the average. Mach. Learn. 72(1-2): 21-37 (2008) - [c14]Maria-Florina Balcan, Steve Hanneke, Jennifer Wortman:
The True Sample Complexity of Active Learning. COLT 2008: 45-56 - [c13]Michael J. Kearns, Jennifer Wortman:
Learning from Collective Behavior. COLT 2008: 99-110 - [c12]John Langford, Alexander L. Strehl, Jennifer Wortman:
Exploration scavenging. ICML 2008: 528-535 - [c11]Nicolas S. Lambert, John Langford, Jennifer Wortman, Yiling Chen, Daniel M. Reeves, Yoav Shoham, David M. Pennock:
Self-financed wagering mechanisms for forecasting. EC 2008: 170-179 - [c10]Yiling Chen, Lance Fortnow, Nicolas S. Lambert, David M. Pennock, Jennifer Wortman:
Complexity of combinatorial market makers. EC 2008: 190-199 - [i1]Yiling Chen, Lance Fortnow, Nicolas S. Lambert, David M. Pennock, Jennifer Wortman:
Complexity of Combinatorial Market Makers. CoRR abs/0802.1362 (2008) - 2007
- [c9]Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman:
Regret to the Best vs. Regret to the Average. COLT 2007: 233-247 - [c8]John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman:
Learning Bounds for Domain Adaptation. NIPS 2007: 129-136 - [c7]Michael J. Kearns, Jinsong Tan, Jennifer Wortman:
Privacy-Preserving Belief Propagation and Sampling. NIPS 2007: 745-752 - [c6]Jennifer Wortman, Yevgeniy Vorobeychik, Lihong Li, John Langford:
Maintaining Equilibria During Exploration in Sponsored Search Auctions. WINE 2007: 119-130 - [c5]Eyal Even-Dar, Michael J. Kearns, Jennifer Wortman:
Sponsored Search with Contexts. WINE 2007: 312-317 - 2006
- [c4]Eyal Even-Dar, Michael J. Kearns, Jennifer Wortman:
Risk-Sensitive Online Learning. ALT 2006: 199-213 - [c3]Koby Crammer, Michael J. Kearns, Jennifer Wortman:
Learning from Multiple Sources. NIPS 2006: 321-328 - 2005
- [c2]Koby Crammer, Michael J. Kearns, Jennifer Wortman:
Learning from Data of Variable Quality. NIPS 2005: 219-226 - 2004
- [c1]Eugene Nudelman, Jennifer Wortman, Yoav Shoham, Kevin Leyton-Brown:
Run the GAMUT: A Comprehensive Approach to Evaluating Game-Theoretic Algorithms. AAMAS 2004: 880-887
Coauthor Index
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