Prediction-Sharing During Training and Inference

Yotam Gafni, Ronen Gradwohl, Moshe Tennenholtz

Abstract: Two firms are engaged in a competitive prediction task. Each firm has two sources of data—labeled historical data and unlabeled inference-time data—and uses the former to derive a prediction model and the latter to make predictions on new instances. We study data-sharing contracts between the firms. The novelty of our study is to introduce and highlight the differences between contracts to share prediction models only, contracts to share inference-time predictions only, and contracts to share both.

External IDs:dblp:conf/sagt/GafniGT24