ixture models represent the superposition of statistical processes, and are natural in machine learning and statistics. In mixed regression, the relationship between input and output is given by one of possibly several different (noisy) linear functions. Thus the solution encodes a combinatorial selection problem, and hence computing it is difficult in the worst case. Even in the average case, little is known in the realm of efficient algorithms with strong statistical guarantees. We give general conditions for linear convergence of…

Classical approaches to causal inference largely rely on the assumption of “lack of interference”, according to which the outcome of each individual does not depend on the treatment assigned to others. In many applications, however, including healthcare interventions in schools, online education, and design of online auctions and political campaigns on social media, assuming lack of interference is untenable. In this talk, Prof. Airoldi will introduce some fundamental ideas to deal with interference in causal analyses, focusing on situations where…