Collaboratively Learning Linear Models with Structured Missing Data Chen Cheng Gary Cheng

We study the problem of collaboratively learning least squares estimates for m agents. Each agent observes a different subset of the features--e.g., containing data collected from sensors of varying resolution. Our goal is to determine how to coordinate the agents in order to produce the best estimator for each agent.