עקוב אחר
Jennifer Wortman Vaughan
Jennifer Wortman Vaughan
Senior Principal Researcher, Microsoft Research, New York City
כתובת אימייל מאומתת בדומיין microsoft.com - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
A theory of learning from different domains‏
S Ben-David, J Blitzer, K Crammer, A Kulesza, F Pereira, JW Vaughan‏
Machine Learning 79 (1-2), 151-175, 2010‏
41512010
Datasheets for datasets‏
T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ...‏
Communications of the ACM 64 (12), 86-92, 2021‏
26952021
Improving fairness in machine learning systems: What do industry practitioners need?‏
K Holstein, J Wortman Vaughan, H Daumé III, M Dudik, H Wallach‏
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems …, 2019‏
9802019
Manipulating and measuring model interpretability‏
F Poursabzi-Sangdeh, DG Goldstein, JM Hofman, JW Wortman Vaughan, ...‏
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021‏
8912021
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning‏
H Kaur, H Nori, S Jenkins, R Caruana, H Wallach, J Wortman Vaughan‏
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020‏
6392020
Learning bounds for domain adaptation‏
J Blitzer, K Crammer, A Kulesza, F Pereira, J Wortman‏
Advances in neural information processing systems, 129-136, 2007‏
6082007
Understanding the Effect of Accuracy on Trust in Machine Learning Models‏
M Yin, J Wortman Vaughan, H Wallach‏
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems …, 2019‏
6072019
Co-designing checklists to understand organizational challenges and opportunities around fairness in ai‏
MA Madaio, L Stark, J Wortman Vaughan, H Wallach‏
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020‏
4832020
Online task assignment in crowdsourcing markets‏
CJ Ho, JW Vaughan‏
Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012‏
4522012
Learning from multiple sources‏
K Crammer, M Kearns, J Wortman‏
Journal of Machine Learning Research 9 (Aug), 1757-1774, 2008‏
3452008
Adaptive task assignment for crowdsourced classification‏
CJ Ho, S Jabbari, JW Vaughan‏
Proceedings of the 30th International Conference on Machine Learning (ICML …, 2013‏
3442013
Run the GAMUT: A comprehensive approach to evaluating game-theoretic algorithms‏
E Nudelman, J Wortman, Y Shoham, K Leyton-Brown‏
AAMAS 4, 880-887, 2004‏
2572004
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research.‏
JW Vaughan‏
Journal of Machine Learning Research 18, 193:1-193:46, 2017‏
2382017
Behavioral experiments on biased voting in networks‏
M Kearns, S Judd, J Tan, J Wortman‏
Proceedings of the National Academy of Sciences 106 (5), 1347-1352, 2009‏
2232009
The true sample complexity of active learning‏
MF Balcan, S Hanneke, JW Vaughan‏
Machine learning 80 (2-3), 111-139, 2010‏
2162010
The true sample complexity of active learning‏
M Balcan, S Hanneke, J Wortman‏
Twenty-First Annual Conference on Learning Theory, 2008‏
2162008
Incentivizing High Quality Crowdwork‏
CJ Ho, A Slivkins, S Suri, JW Vaughan‏
Proceedings of the 24th International Conference on World Wide Web, 419-429, 2015‏
2102015
The Disparate Effects of Strategic Manipulation‏
L Hu, N Immorlica, JW Vaughan‏
ACM Conference on Fairness, Accountability, and Transparency (FAT*), 2019‏
2002019
Adaptive contract design for crowdsourcing markets: Bandit algorithms for repeated principal-agent problems‏
CJ Ho, A Slivkins, JW Vaughan‏
Proceedings of the fifteenth ACM conference on Economics and computation …, 2014‏
1602014
Toward fairness in AI for people with disabilities: a research roadmap‏
A Guo, E Kamar, JW Vaughan, H Wallach, MR Morris‏
ACM SIGACCESS Accessibility and Computing, 1-1, 2020‏
1592020
המערכת אינה יכולה לבצע את הפעולה כעת. נסה שוב מאוחר יותר.
מאמרים 1–20