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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 - [i48]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) - [i47]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) - [i46]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) - [i45]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) - [i44]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) - [i43]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) - 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]