Abstract
This talk focuses on one of the most fundamental problems in private computation that arises in many practical scenarios: the Private Linear Computation (PLC) problem. In PLC, the objective is to compute a single linear combination of data items while minimizing the amount of data that needs to be downloaded, all while preserving data access privacy. We discuss several variations of the PLC problem, including different privacy requirements, the use of side information, and single-provider versus multi-provider scenarios. For each case, we present the state-of-the-art achievability schemes, converse proof techniques, and open research problems.