Summary of Practical Marketplace Optimization at Uber Using Causally-informed Machine Learning, by Bobby Chen et al.
Practical Marketplace Optimization at Uber Using Causally-Informed Machine Learning
by Bobby Chen, Siyu Chen, Jason Dowlatabadi, Yu Xuan Hong, Vinayak Iyer, Uday Mantripragada, Rishabh Narang, Apoorv Pandey, Zijun Qin, Abrar Sheikh, Hongtao Sun, Jiaqi Sun, Matthew Walker, Kaichen Wei, Chen Xu, Jingnan Yang, Allen T. Zhang, Guoqing Zhang
First submitted to arxiv on: 26 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Machine Learning (stat.ML)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary As a machine learning educator writing for a technical audience, I summarize the abstract as follows: This research paper presents an end-to-end machine learning and optimization procedure to automate budget decision-making for cities at Uber. The goal is to maximize business value by understanding the impact of lever budget changes and estimating cost efficiency. The authors propose state-of-the-art deep learning estimator based on S-Learner and novel tensor B-Spline regression model, using ADMM and primal-dual interior point convex optimization to solve high-dimensional optimization problems. This approach substantially improves Uber’s resource allocation efficiency. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary For curious learners or general audiences without a technical background, I simplify the summary as follows: Imagine you’re trying to manage a big company like Uber, and you need to make decisions about how to spend your money to get the best results. The researchers developed a new way to do this using special computer programs that can learn from data and make good choices. This new method helps Uber make better decisions about where to put their resources, which means they can be more efficient and achieve their goals. |
Keywords
» Artificial intelligence » Deep learning » Machine learning » Optimization » Regression
