KDD
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KDD: Graph neural networks, fairness, and inclusivity
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As general chair of this year’s ACM Conference on Knowledge Discovery and Data Mining (KDD), Huzefa Rangwala, a senior manager at the Amazon Machine ...

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Scaling graph-neural-network training with CPU-GPU clusters
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Graphs are a useful way to represent data, since they capture connections between data items, and graph neural networks (GNNs) are an increasingly popular ...

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Amazon product query competition draws more than 9,200 submissions
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At this year’s Conference on Knowledge Discovery and Data Mining (KDD), Amazon hosted a workshop in which we announced the results of our ESCI Challenge for ...

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Amazon scientists win best-paper award for ad auction simulator
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Opportunities to show ads on the worldwide web are typically sold in real time through advertising auctions, held billions of times per day, every day. A ...

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Leveraging transformers to improve product retrieval results
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When a customer clicks on an item in a list of product-search results, it implies that that item is better than those not clicked. “Learning to rank” models ...

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KDD 2023: Graph neural networks’ new frontiers
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In 2021 and 2022, when Amazon Science asked members of the program committees of the Knowledge Discovery and Data Mining Conference (KDD) to discuss the ...

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Compressing token-embedding matrices for language models
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Pretrained language models (PLMs) like BERT, RoBERTa, and DeBERTa, when fine-tuned on task-specific data, have demonstrated exceptional performance across a ...

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