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KDD 20222022Speed of delivery is critical for the success of e-commerce platforms. Faster delivery promise to the customer results in increased conversion and revenue. There are typically two mechanisms to control the delivery speed - a) replication of products across warehouses, and b) air-shipping the product. In this paper, we present a machine learning based framework to recommend air-shipping eligibility for products
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ICML 20222022Recovering global rankings from pairwise comparisons has wide applications from time synchronization to sports team ranking. Pairwise comparisons corresponding to matches in a competition can be construed as edges in a directed graph (digraph), whose nodes represent e.g. competitors with an unknown rank. In this paper, we introduce neural networks into the ranking recovery problem by proposing the so-called
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ICML 20222022The idea behind object-centric representation learning is that natural scenes can better be modeled as compositions of objects and their relations as opposed to distributed representations. This inductive bias can be injected into neural networks to potentially improve systematic generalization and performance of downstream tasks in scenes with multiple objects. In this paper, we train state-of-the-art
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EURASIP Journal on Audio, Speech, and Music Processing2022Subtitles are a crucial component of Digital Entertainment Content (DEC such as movies and TV shows) localization. With ever increasing catalog (≈ 2M titles) and localization expansion (30+ languages), automated subtitle quality checks becomes paramount. Being a manual creation process, subtitles can have errors such as missing transcriptions, out-of-sync subtitle blocks with the audio and incorrect translations
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KDD 20222022A/B tests, also known as online controlled experiments, have been used at scale by data-driven enterprises to guide decisions and test innovative ideas. Meanwhile, non-stationarity, such as the time-of-day effect, can commonly arise in various business metrics. We show that inadequately addressing non-stationarity can cause A/B tests to be statistically inefficient or invalid, leading to wrong conclusions
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