Showing results 1 - 10 of 10
2024, Paper: "Comparison data elicited from people are fundamental to many machine learning tasks, including reinforcement learning from human feedback for large language models鈥�
June 24, 2021, Paper: "There is evidence that prediction markets are useful tools to aggregate information on researchers鈥� beliefs about scientific results including the outcome鈥�
2020, Paper, "There is evidence that prediction markets are useful tools to aggregate information about researchers鈥� beliefs about scientific results including forecasting the鈥�
Welfare and Distributional Impacts of Fair Classification. Yiling Chen, 2018, Paper, "Current methodologies in machine learning analyze the effects of various statistical鈥�
A Short-term Intervention for Long-term Fairness in the Labor Market. Lily Hu, Yiling Chen, November 30, 2017, Paper, "The persistence of racial inequality in the U.S. labor鈥�
Fairness at Equilibrium in the Labor Market. Yiling Chen, July 5, 2017, Paper, "Recent literature on computational notions of fairness has been broadly divided into two鈥�
Learning to Incentivize: Eliciting Effort via Output Agreement. Yang Liu, Yiling Chen, April 19, 2016, Paper. "In crowdsourcing when there is a lack of verification for鈥�
Market Manipulation with Outside Incentives. Yiling Chen, March 1, 2014, Paper. "Much evidence has shown that prediction markets can effectively aggregate dispersed information鈥�
The Effects of Performance-Contingent Financial Incentives in Online Labor Markets. Yiling Chen, July 2013, Paper. "Online labor markets such as Amazon Mechanical Turk (MTurk)鈥�
What you jointly know determines how you act: strategic interactions in prediction markets. Yiling Chen, June 2013, Paper. "The primary goal of a prediction market is to elicit鈥�