Bandit problems
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3 important themes from Amazon’s 2019 NeurIPS papers
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Last year, the first 2,000-2,500 publicly released tickets to the Conference on Neural Information Processing Systems, or NeurIPS, sold out in 12 ...

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Amazon scientist Matthias Seeger receives ICML “test of time” award
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Matthias Seeger, a principal applied scientist in Amazon’s Berlin office, and three coauthors have received the ICML 2020 test of time award for a paper ...

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ICML: “Test of time” paper shows how times have changed
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Amazon researchers have nine new papers at this year’s International Conference on Machine Learning (ICML), one of the top conferences in AI. Matthias ...

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A general approach to solving bandit problems
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Bandit problems are problems in which an agent interacting with the environment tries to simultaneously maximize some reward and learn how to maximize that ...

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NeurIPS: Shipra Agrawal on the appeal of reinforcement learning
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As deep neural networks have come to dominate AI, the Conference on Neural Information Processing Systems (NeurIPS 2020) has become the most popular ...

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Two Amazon papers were runners-up for best-paper awards at AAAI
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At the meeting of the Association for the Advancement of Artificial Intelligence (AAAI) earlier this year, papers whose coauthors included Amazon ...

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Decisions, decisions: Lihong Li’s Amazon Ads reinforcement learning research
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How does the Amazon Store know what products and offers to display to a customer? Part of the answer involves reinforcement learning, a type of machine ...

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Lihong Li wins 2023 Seoul Test of Time Award
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Lihong Li, a senior principal scientist in Amazon Ads, has won the 2023 Seoul Test of Time award for the 2010 paper “A Contextual-Bandit Approach to ...

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A quick guide to Amazon’s papers at ICML
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At this year's International Conference on Machine Learning (ICML), Amazon researchers have several papers on bandit problems and differential privacy, two ...

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