Jennifer Wortman Vaughan

135 papers A* 34A 5B 2C 1Journal 83Unranked 10
YearRankTypeTitle / Venue / Authors
2026 A* conf
"Helping Me Versus Doing It for Me": Designing for Agency in LLM-Infused Writing Tools for Science Journalism.
CHI
Sachita Nishal, Mina Lee, Nicholas Diakopoulos, Jennifer Wortman Vaughan
2025 A* conf
Canvil: Designerly Adaptation for LLM-Powered User Experiences.
CHI
K. J. Kevin Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy X. Zhang, David W. McDonald
2025 — conf
Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline.
FAccT
Shivani Kapania, Stephanie Ballard, Alex Kessler, Jennifer Wortman Vaughan
2025 J jnl
Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline.
CoRR
Shivani Kapania, Stephanie Ballard, Alex Kessler, Jennifer Wortman Vaughan
2025 A* conf
Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies.
CHI
Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao, Tania Lombrozo, Olga Russakovsky
2025 J jnl
Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies.
CoRR
Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao, Tania Lombrozo, Olga Russakovsky
2025 J jnl
Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions.
ACM Trans. Comput. Hum. Interact.
Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
2025 — conf
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge.
ICML (Position Papers)
Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J. Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2025 J jnl
Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge.
CoRR
Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2025 J jnl
Supporting Industry Computing Researchers in Assessing, Articulating, and Addressing the Potential Negative Societal Impact of Their Work.
Proc. ACM Hum. Comput. Interact.
Wesley Hanwen Deng, Solon Barocas, Jennifer Wortman Vaughan
2024 — conf
"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust.
FAccT
Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan
2024 J jnl
"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust.
CoRR
Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan
2024 J jnl
(De)Noise: Moderating the Inconsistency Between Human Decision-Makers.
CoRR
Nina Grgic-Hlaca, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan
2024 J jnl
(De)Noise: Moderating the Inconsistency Between Human Decision-Makers.
Proc. ACM Hum. Comput. Interact.
Nina Grgic-Hlaca, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan
2024 J jnl
An Equivalence Between Fair Division and Wagering Mechanisms.
Manag. Sci.
Rupert Freeman, Jens Witkowski, Jennifer Wortman Vaughan, David M. Pennock
2024 J jnl
Canvil: Designerly Adaptation for LLM-Powered User Experiences.
CoRR
K. J. Kevin Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy X. Zhang, David W. McDonald
2024 J jnl
Challenges in Human-Agent Communication.
CoRR
Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi, Eric Horvitz, Adam Fourney, Hussein Mozannar, Victor Dibia, Daniel S. Weld
2024 J jnl
Dimensions of Generative AI Evaluation Design.
CoRR
P. Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alexandra Chouldechova, Hanna M. Wallach
2024 J jnl
Evaluating Generative AI Systems is a Social Science Measurement Challenge.
CoRR
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
2024 J jnl
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice.
CoRR
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 A. Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, Katherine Lee
2024 J jnl
Supporting Industry Computing Researchers in Assessing, Articulating, and Addressing the Potential Negative Societal Impact of Their Work.
CoRR
Wesley Hanwen Deng, Solon Barocas, Jennifer Wortman Vaughan
2024 J jnl
Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist.
Proc. ACM Hum. Comput. Interact.
Michael A. Madaio, Jingya Chen, Hanna M. Wallach, Jennifer Wortman Vaughan
2023 J jnl
AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap.
CoRR
Q. Vera Liao, Jennifer Wortman Vaughan
2023 A* conf
Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience.
CHI
Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan
2023 J jnl
Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience.
CoRR
Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan
2023 A* conf
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse.
CHI
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
2023 J jnl
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse.
CoRR
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
2023 J jnl
Generation Probabilities Are Not Enough: Exploring the Effectiveness of Uncertainty Highlighting in AI-Powered Code Completions.
CoRR
Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
2023 J jnl
Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits.
SIAM J. Comput.
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
2023 J jnl
Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment.
CoRR
Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan
2023 J jnl
Incentive-Compatible Forecasting Competitions.
Manag. Sci.
Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
2023 J jnl
Open Datasheets: Machine-readable Documentation for Open Datasets and Responsible AI Assessments.
CoRR
Anthony Cintron Roman, Jennifer Wortman Vaughan, Valerie See, Steph Ballard, Nicolas Schifano, Jehu Torres Vega, Caleb Robinson, Juan M. Lavista Ferres
2023 J jnl
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations.
CoRR
Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
2023 J jnl
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations.
Proc. ACM Hum. Comput. Interact.
Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
2022 J jnl
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support.
Proc. ACM Hum. Comput. Interact.
Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach
2022 J jnl
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?
CoRR
Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah
2022 A* conf
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values.
KDD
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2022 J jnl
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values.
CoRR
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2022 J jnl
Interpretable Distribution Shift Detection using Optimal Transport.
CoRR
Neha Hulkund, Nicolò Fusi, Jennifer Wortman Vaughan, David Alvarez-Melis
2022 — conf
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research.
FAccT
Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan
2022 J jnl
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research.
CoRR
Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan
2022 J jnl
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata.
CoRR
Amy Heger, Elizabeth B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
2022 J jnl
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata.
Proc. ACM Hum. Comput. Interact.
Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
2021 J jnl
A Human-Centered Interpretability Framework Based on Weight of Evidence.
CoRR
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
2021 A* ed.
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual.
NeurIPS
Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan
2021 J jnl
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support.
CoRR
Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach
2021 J jnl
Datasheets for datasets.
Commun. ACM
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
2021 C conf
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs.
AIES
Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach
2021 J jnl
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs.
CoRR
Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach
2021 B conf
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence.
HCOMP
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
2021 J jnl
GAM Changer: Editing Generalized Additive Models with Interactive Visualization.
CoRR
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2021 J jnl
Incentive-Compatible Forecasting Competitions.
CoRR
Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
2021 — conf
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning.
DaSH@KDD
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan
2021 A* conf
Manipulating and Measuring Model Interpretability.
CHI
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
2021 J jnl
Responsible computing during COVID-19 and beyond.
Commun. ACM
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
2021 J jnl
Summarize with Caution: Comparing Global Feature Attributions.
IEEE Data Eng. Bull.
Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna M. Wallach, Jennifer Wortman Vaughan
2021 J jnl
Truthful aggregation of budget proposals.
J. Econ. Theory
Rupert Freeman, David M. Pennock, Dominik Peters, Jennifer Wortman Vaughan
2020 A* conf
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI.
CHI
Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach
2020 J jnl
Greedy Algorithm almost Dominates in Smoothed Contextual Bandits.
CoRR
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
2020 A* conf
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning.
CHI
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan
2020 J jnl
Mathematical Foundations for Social Computing.
CoRR
Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
2020 A* conf
No-Regret and Incentive-Compatible Online Learning.
ICML
Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan
2020 J jnl
No-Regret and Incentive-Compatible Online Learning.
CoRR
Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan
2020 J jnl
Oracle-efficient Online Learning and Auction Design.
J. ACM
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2020 J jnl
The Possibilities and Limitations of Private Prediction Markets.
ACM Trans. Economics and Comput.
Rachel Cummings, David M. Pennock, Jennifer Wortman Vaughan
2020 J jnl
Toward fairness in AI for people with disabilities SBG@a research roadmap.
ACM SIGACCESS Access. Comput.
Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris
2019 A* conf
An Equivalence between Wagering and Fair-Division Mechanisms.
AAAI
Rupert Freeman, David M. Pennock, Jennifer Wortman Vaughan
2019 A* conf
Group Fairness for the Allocation of Indivisible Goods.
AAAI
Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan
2019 A* conf
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?
CHI
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
2019 B ed.
Proceedings of the Seventh AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2019, Stevenson, WA, USA, October 28-30, 2019.
HCOMP
Edith Law, Jennifer Wortman Vaughan
2019 — conf
The Disparate Effects of Strategic Manipulation.
FAT
Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
2019 J jnl
Toward Fairness in AI for People with Disabilities: A Research Roadmap.
CoRR
Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris
2019 A* conf
Truthful Aggregation of Budget Proposals.
EC
Rupert Freeman, David M. Pennock, Dominik Peters, Jennifer Wortman Vaughan
2019 J jnl
Truthful Aggregation of Budget Proposals.
CoRR
Rupert Freeman, David M. Pennock, Dominik Peters, Jennifer Wortman Vaughan
2019 A* conf
Understanding the Effect of Accuracy on Trust in Machine Learning Models.
CHI
Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach
2019 A conf
Using Search Queries to Understand Health Information Needs in Africa.
ICWSM
Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz
2019 J jnl
Weight of Evidence as a Basis for Human-Oriented Explanations.
CoRR
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach
2018 J jnl
Datasheets for Datasets.
CoRR
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
2018 J jnl
Improving fairness in machine learning systems: What do industry practitioners need?
CoRR
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
2018 A* conf
Incentive-Compatible Forecasting Competitions.
AAAI
Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
2018 J jnl
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets.
ACM Trans. Economics and Comput.
Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan
2018 J jnl
Manipulating and Measuring Model Interpretability.
CoRR
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
2018 J jnl
The Disparate Effects of Strategic Manipulation.
CoRR
Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
2018 A* conf
The Externalities of Exploration and How Data Diversity Helps Exploitation.
COLT
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
2018 J jnl
The Externalities of Exploration and How Data Diversity Helps Exploitation.
CoRR
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
2018 J jnl
Using Search Queries to Understand Health Information Needs in Africa.
CoRR
Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz
2017 — conf
A Decomposition of Forecast Error in Prediction Markets.
NIPS
Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan
2017 J jnl
A Decomposition of Forecast Error in Prediction Markets.
CoRR
Miroslav Dudík, Sébastien Lahaie, Ryan M. Rogers, Jennifer Wortman Vaughan
2017 J jnl
Incentives and the crowd.
XRDS
Jennifer Wortman Vaughan
2017 J jnl
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research.
J. Mach. Learn. Res.
Jennifer Wortman Vaughan
2017 A* conf
Oracle-Efficient Online Learning and Auction Design.
FOCS
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2017 A* conf
The Double Clinching Auction for Wagering.
EC
Rupert Freeman, David M. Pennock, Jennifer Wortman Vaughan
2017 — conf
Tutorial: Making Better Use of the Crowd.
ACL (Tutorial Abstracts)
Jennifer Wortman Vaughan
2016 J jnl
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems.
J. Artif. Intell. Res.
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
2016 A conf
Bounded Rationality in Wagering Mechanisms.
UAI
David M. Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2016 J jnl
Mathematical foundations for social computing.
Commun. ACM
Yiling Chen, Arpita Ghosh, Michael J. Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
2016 J jnl
Oracle-Efficient Learning and Auction Design.
CoRR
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2016 A* conf
The Communication Network Within the Crowd.
WWW
Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan
2016 A* conf
The Possibilities and Limitations of Private Prediction Markets.
EC
Rachel Cummings, David M. Pennock, Jennifer Wortman Vaughan
2016 J jnl
The Possibilities and Limitations of Private Prediction Markets.
CoRR
Rachel Cummings, David M. Pennock, Jennifer Wortman Vaughan
2015 J jnl
An axiomatic characterization of wagering mechanisms.
J. Econ. Theory
Nicolas S. Lambert, John Langford, Jennifer Wortman Vaughan, Yiling Chen, Daniel M. Reeves, Yoav Shoham, David M. Pennock
2015 A* conf
Incentivizing High Quality Crowdwork.
WWW
Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
2015 J jnl
Incentivizing High Quality Crowdwork.
CoRR
Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
2015 J jnl
Incentivizing high quality crowdwork.
SIGecom Exch.
Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
2015 A* conf
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets.
EC
Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan
2014 A* conf
A general volume-parameterized market making framework.
EC
Jacob D. Abernethy, Rafael M. Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
2014 J jnl
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems.
CoRR
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
2014 A* conf
Adaptive contract design for crowdsourcing markets: bandit algorithms for repeated principal-agent problems.
EC
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
2014 J jnl
Computational social science and social computing.
Mach. Learn.
Winter A. Mason, Jennifer Wortman Vaughan, Hanna M. Wallach
2014 A conf
Market Making with Decreasing Utility for Information.
UAI
Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan
2014 J jnl
Market Making with Decreasing Utility for Information.
CoRR
Miroslav Dudík, Rafael M. Frongillo, Jennifer Wortman Vaughan
2014 A* conf
Removing arbitrage from wagering mechanisms.
EC
Yiling Chen, Nikhil R. Devanur, David M. Pennock, Jennifer Wortman Vaughan
2013 — conf
Adaptive Task Assignment for Crowdsourced Classification.
ICML (1)
Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
2013 A* conf
An axiomatic characterization of adaptive-liquidity market makers.
EC
Xiaolong Li, Jennifer Wortman Vaughan
2013 A* conf
Cost function market makers for measurable spaces.
EC
Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
2013 J jnl
Efficient Market Making via Convex Optimization, and a Connection to Online Learning.
ACM Trans. Economics and Comput.
Jacob D. Abernethy, Yiling Chen, Jennifer Wortman Vaughan
2013 J jnl
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges (Position Paper).
CoRR
Aleksandrs Slivkins, Jennifer Wortman Vaughan
2013 J jnl
Online decision making in crowdsourcing markets: theoretical challenges.
SIGecom Exch.
Aleksandrs Slivkins, Jennifer Wortman Vaughan
2012 J jnl
Censored Exploration and the Dark Pool Problem
CoRR
Kuzman Ganchev, Michael J. Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan
2012 J jnl
Designing Informative Securities
CoRR
Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
2012 A conf
Designing Informative Securities.
UAI
Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
2012 A* conf
Online Task Assignment in Crowdsourcing Markets.
AAAI
Chien-Ju Ho, Jennifer Wortman Vaughan
2012 — conf
Towards Social Norm Design for Crowdsourcing Markets.
HCOMP@AAAI
Chien-Ju Ho, Yu Zhang, Jennifer Wortman Vaughan, Mihaela van der Schaar
2011 A* conf
An optimization-based framework for automated market-making.
EC
Jacob D. Abernethy, Yiling Chen, Jennifer Wortman Vaughan
2010 J jnl
A New Understanding of Prediction Markets Via No-Regret Learning
CoRR
Yiling Chen, Jennifer Wortman Vaughan
2010 A* conf
A new understanding of prediction markets via no-regret learning.
EC
Yiling Chen, Jennifer Wortman Vaughan
2010 J jnl
A theory of learning from different domains.
Mach. Learn.
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan
2010 J jnl
An Optimization-Based Framework for Automated Market-Making
CoRR
Jacob D. Abernethy, Yiling Chen, Jennifer Wortman Vaughan
2010 J jnl
Censored exploration and the dark pool problem.
Commun. ACM
Kuzman Ganchev, Yuriy Nevmyvaka, Michael J. Kearns, Jennifer Wortman Vaughan
2010 J jnl
Connections between markets and learning.
SIGecom Exch.
Yiling Chen, Jennifer Wortman Vaughan
2010 J jnl
Evolution with Drifting Targets
CoRR
Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan
2010 A* conf
Evolution with Drifting Targets.
COLT
Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan
2010 A* conf
Regret Minimization With Concept Drift.
COLT
Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jennifer Wortman Vaughan
2010 J jnl
The true sample complexity of active learning.
Mach. Learn.
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