Abstract: 

In this workshop, we will provide an overview of techniques for matrix and tensor estimation. We will showcase a wide variety of applications for matrix estimation in analyzing large heterogeneous datasets that may have missing or incorrect entries, including retail, causal inference, sports and networks. These applications will form the basis for some practical demos with opportunities for hands-on experience. Subsequently we will explain the intuition for matrix and tensor estimation algorithms, with a focus on collaborative filtering.

Bio: 

Muhammad Jehangir Amjad is a Software Engineer in the Network Infrastructure team at Google. He joined Google from MIT where he has an appointment as a Lecturer of Machine Learning in CSAIL. Jehangir received his PhD from the Operations Research Center (ORC) and Laboratory of Information and Decision Systems (LIDS) at MIT, under the supervision of Prof Devavrat Shah. He received his BSE in Electrical Engineering from Princeton University.