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cs.LG2025
Consistency Conditions for Differentiable Surrogate Losses
Drona Khurana, Anish Thilagar, Dhamma Kimpara +1
The statistical consistency of surrogate losses for discrete prediction tasks is often checked via the condition of calibration. However, directly verifying calibration can be ardu…
cs.LG2024
Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
Mary Monroe, Anish Thilagar, Melody Hsu +1
In forecasting competitions, the traditional mechanism scores the predictions of each contestant against the outcome of each event, and the contestant with the highest total score…
cs.LG2021
Efficient Competitions and Online Learning with Strategic Forecasters
Rafael Frongillo, Robert Gomez, Anish Thilagar +1
Winner-take-all competitions in forecasting and machine-learning suffer from distorted incentives. Witkowski et al. 2018 identified this problem and proposed ELF, a truthful mechan…