Recommendations systems play a central role in improving customer experience on the Amazon retail website. Commonly, Learning-to-Rank (LTR) methods are employed to rank content, however these methods are subject to bias inherent in the observational data that they use for training. This paper…
Low-quality listings and bad actor behavior in online retail websites threatens e-commerce business as these result in sub-optimal buying experience and erode customer trust. When a new listing is created, how to tell it has good quality? Is the method effective, fast, and scalable? Previous…
Despite the increasing relevance of forecasting methods, causal implications of these algorithms remain largely unexplored. This is concerning considering that, even under simplifying assumptions such as causal sufficiency, the statistical risk of a model can differ significantly from its causal…
Adaptive experimental design methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N testing methods. This paper shares lessons learned regarding the challenges and pitfalls of naively using adaptive…
Understanding and representing real-world places (physical locations where drivers can deliver packages) is key to successfully and efficiently delivering packages to customer’s doorstep. Prerequisite to this is the task of capturing similarity and relatedness between places. Intuitively, places…
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