Hyperparameter optimization
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How SageMaker’s algorithms help democratize machine learning
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SageMaker is a service from Amazon Web Services that lets customers quickly and easily build machine learning models for deployment in the cloud. It ...

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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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When does transfer learning work?
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Transfer learning is a widely used technique for improving the performance of neural networks when labeled training data is scarce. Before a network is ...

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Amazon researchers win best-paper award for helping promote fairness in AI
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Last week, at the seventh Workshop on Automated Machine Learning (AutoML) at the International Conference on Machine Learning, Amazon researchers won a ...

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AWS releases code to help reduce bias in machine learning models
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In recent years, algorithmic bias has become an important research topic in machine learning. Sometimes, because of imbalances in training data or other ...

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A hyperparameter optimization library for reproducible research
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Recent algorithmic advances and hardware innovations have made it possible to train deep neural networks with billions of parameters. The networks’ ...

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Amazon wins best-paper award at first AutoML conference
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At the first annual Conference on Automated Machine Learning (AutoML), my colleagues and I won a best-paper award for a new way to decide when to terminate ...

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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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Learning to learn learning-rate schedules
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Training a machine learning model can be thought of as exploring a landscape that maps settings of the model parameters against average error rate. The goal ...

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