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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...
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...
Recent algorithmic advances and hardware innovations have made it possible to train deep neural networks with billions of parameters. The networks’ performance, however, depends in part...
In recent years, algorithmic bias has become an important research topic in machine learning. Sometimes, because of imbalances in training data or other factors, machine learning...
Last week, at the seventh Workshop on Automated Machine Learning (AutoML) at the International Conference on Machine Learning, Amazon researchers won a best-paper award for a...
Transfer learning is a widely used technique for improving the performance of neural networks when labeled training data is scarce. Before a network is trained on...
Amazon researchers have nine new papers at this year’s International Conference on Machine Learning (ICML), one of the top conferences in AI. Matthias Seeger, a principal...
SageMaker is a service from Amazon Web Services that lets customers quickly and easily build machine learning models for deployment in the cloud. It includes a...