118 citations · 210 across the 11 of their papers we have counts for
11 papers
Balancing Approach for Causal Inference at Scale
Sicheng Lin, Meng Xu, Xi Zhang +3
With the modern software and online platforms to collect massive amount of data, there is an increasing demand of applying causal inference methods at large scale when randomized e…
How to Measure Your App: A Couple of Pitfalls and Remedies in Measuring App Performance in Online Controlled Experiments
Yuxiang Xie, Meng Xu, Evan Chow +1
Effectively measuring, understanding, and improving mobile app performance is of paramount importance for mobile app developers. Across the mobile Internet landscape, companies run…
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
Xianfeng Tang, Yozen Liu, Neil Shah +3
With the rapid growth and prevalence of social network applications (Apps) in recent years, understanding user engagement has become increasingly important, to provide useful insig…
I Know You'll Be Back: Interpretable New User Clustering and Churn Prediction on a Mobile Social Application
Carl Yang, Xiaolin Shi, Jie Luo +1
As online platforms are striving to get more users, a critical challenge is user churn, which is especially concerning for new users. In this paper, by taking the anonymous large-s…
Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat
Yozen Liu, Xiaolin Shi, Lucas Pierce +1
While mobile social apps have become increasingly important in people's daily life, we have limited understanding on what motivates users to engage with these apps. In this paper,…
False Discovery Rate Controlled Heterogeneous Treatment Effect Detection for Online Controlled Experiments
Yuxiang Xie, Nanyu Chen, Xiaolin Shi
Online controlled experiments (a.k.a. A/B testing) have been used as the mantra for data-driven decision making on feature changing and product shipping in many Internet companies.…