Customer-obsessed science
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September 30, 2024From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money.
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September 19, 2024“Agentic workflows” that use multiple, fine-tuned smaller LLMs — rather than one large one — can improve efficiency.
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September 16, 2024A position paper presented at ACL proposes a framework for more-accurate human evaluation of LLMs.
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September 29 - October 4, 2024
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October 21 - 25, 2024
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September 25, 2024
Now open until November 6, Amazon Research Awards will be seeking proposals in the following research areas: AI for Information Security, Automated Reasoning, AWS AI, AWS Cryptography, and Sustainability.
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RecSys 2023 Workshop on Learning and Evaluating Recommendations with Impressions (LERI 2023)2023Addressing the position bias is of pivotal importance for performing unbiased off-policy training and evaluation in Learning To Rank (LTR). This requires accurate estimates of the probabilities of the users examining the slots where items are displayed, which in many applications is likely to depend on multiple factors, e.g. the screen size. This leads to a position-bias curve that is no longer constant
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CP2023- International Conference on Principles and Practice of Constraint Programming2023Due to the limited connectivity of gate model quantum devices, logical quantum circuits must be compiled to target hardware before they can be executed. Often, this process involves the insertion of SWAP gates into the logical circuit, usually increasing the depth of the circuit, achieved by solving a so-called qubit assignment and routing problem. Recently, a number of integer linear programming (ILP)
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RecSys 2023 Workshop on Causality, Counterfactuals & Sequential Decision-Making (CONSEQUENCES)2023For industrial learning-to-rank (LTR) systems, it is common that the output of a ranking model is modified, either as a results of post-processing logic that enforces business requirements, or as a result of unforeseen design flaws or bugs present in real-world production systems. This poses a challenge for deploying off-policy learning and evaluation methods, as these often rely on the assumption that
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IEEE CDC 20232023Online advertising is typically implemented via real-time bidding, and advertising campaigns are then defined as extremely high-dimensional optimization problems. Advertisers often define a campaign by an order consisting of multiple lines. Campaign delivery constraints may be imposed on the order as a whole and on each ad line. E.g., there may be budget and cost per click constraints on the order and on
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KDD 2023 International Workshop on Multimodal Learning2023In this paper, we study the problem of detecting objects with rich textual features from images. One such example is to detect stopwatch regions from sports videos. We propose a novel approach that combines image feature with text features for object detection, and benchmark against traditional OCR-based method and object detection method using image feature only. In particular, we modify the Faster R-CNN
Resources
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We collaborate with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly.
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Learn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.