Researchers have determined how to build reliable machine learning ... "Using a simple model, you might be able to enforce some of the physics that you already know into the training data set ...

A machine learning model that processes text must not only ... computing hardware and graphics processing units (GPU) in training and inference. Second, they could not handle long sequences ...

The result is a machine learning framework that is easier to work with—for example, by using the relatively simple Keras API for model training—and more performant. Distributed training is ...

Normally, developing a machine learning model would require several rounds of training, using the power of a cluster of linked computers. In contrast, the team's tiny model completed the training ...

With the increased model size and larger data sets, standardized tools like MLPerf Training and MLPerf Inference are more crucial than ever. Machine learning model performance must be measured ...

Machine learning is ... males (because of biases in the training population). Machine learning depends on a number of algorithms for turning a data set into a model. Which algorithm works best ...

Data poisoning or model poisoning attacks involve polluting a machine learning model’s training data. Data poisoning is considered an integrity attack because tampering with the training data ...