"Randomized experiments are increasingly central to innovation in many fields. In the tech sector, major platforms run thousands of experiments (called A/B tests) each year on tens of millions of users at any given time and use the results to screen ...

We build a natural connection between the learning problem, co-training, and forecast elicitation without verification (related to peer-prediction) and address them simultaneously using the same information theoretic approach. In co-training/multiview ...

A central question of crowdsourcing is how to elicit expertise from agents. This is even more difficult when answers cannot be directly verified. A key challenge is that sophisticated agents may strategically withhold effort or information when they ...