ORIE Special Seminar: Wanning Chen (Stanford)

Description

Learning to Recommend Using Non-Uniform Data

Learning user preferences for products based on their past purchases or reviews is at the cornerstone of modern recommendation engines. One complication in this learning task is that some users are more likely to purchase products or review them, and some products are more likely to be purchased or reviewed by the users. This non-uniform pattern degrades the power of many existing recommendation algorithms, as they assume that the observed data is sampled uniformly at random among user-product pairs. In addition, existing literature on modeling non-uniformity either assume user interests are independent of the products or lacks theoretical understanding. In this paper, we first model the user-product preferences as a partially observed matrix with a non-uniform observation pattern. Next, building on the literature about low-rank matrix estimation, we introduce a new weighted trace-norm penalized regression to predict unobserved values of the matrix. We then prove an upper bound for the prediction error of our proposed approach. Our upper bound is a function of a number of parameters that are based on a certain weight matrix that depends on the joint distribution of users and products. Utilizing this observation, we introduce a new optimization problem to select a weight matrix that minimizes the upper bound on the prediction error. The final product is a new estimator, NU-Recommend, that outperforms existing methods in both synthetic and real datasets.

Bio:
Wanning Chen is a Ph.D. candidate at Stanford University, where she is part of the Operations, Information and Technology group at the Graduate School of Business, under the supervision of Professor Mohsen Bayati. Her research focuses on developing a statistical methodology for data-driven decision-making. In particular, she designs novel machine learning algorithms for problems where the underlying data has a natural matrix structure. Prior to Stanford University, Wanning obtained her B.A. in mathematics from Pomona College.