Causal inference
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Economics Nobelist on causal inference
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Since 2013, Amazon has held an annual internal conference, the Amazon Machine Learning Conference (AMLC), where machine learning practitioners from around ...

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Removing selection bias from evaluation of recommendations
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More than 60% of sales in Amazon’s store come from independent sellers. One of the big drivers of this growth has been Fulfillment by Amazon, or FBA, which ...

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Amazon helps create first conference on causal learning and reasoning
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The Causal Learning and Reasoning (CLeaR) conference — the first international conference on causal learning and reasoning — will launch next week in ...

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Amazon at ICLR: Graphs, time series, and more
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Time series forecasting and graph representations of data are both major topics of research at Amazon: time series forecasting is crucial to both supply ...

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AWS contributes novel causal machine learning algorithms to DoWhy Python library
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We are excited to announce that we are open-sourcing causal machine learning (ML) algorithms that are the result of years of Amazon research on graphical ...

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New workshop to help bring causal reasoning to recommendation systems
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The ACM Conference on Recommender Systems (RecSys) is the premier conference in the field of recommender systems, with recent editions attracting well over ...

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New method identifies the root causes of statistical outliers
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Outliers are rare observations where a system deviates from its usual behavior. They arise in many real-world applications (e.g., medicine, finance) and ...

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ICML: Where causality meets machine learning
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Dominik Janzing, a principal research scientist with Amazon Web Services, is a coauthor on four of Amazon’s 18 papers at this year’s International ...

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Honorable mention to Amazon researchers for ICML test-of-time award
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The Worldwide Design Engineering (WWDE) organization delivers innovative, effective and efficient ...

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Causal inference when treatments are continuous variables
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In scientific and business endeavors, we are often interested in the causal effect of a treatment — say, changing the font of a web page — on a response ...

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