“Abstract—Large-scale distributed deep learning training has enabled developments of more complex deep neural network models to learn from larger datasets for sophisticated tasks. In particular, ...

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

This is Google’s animated illustration of how tensors flow from node to node through the edges of a data flow graph. TensorFlow currently runs on Ubuntu Linux, MacOS, Android, iOS, and Raspberry ...

Next, based upon the flow chart of the map-based localization algorithm, a localizability predictor, which is composed of three different models, is designed to predict the entropy. Here a ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

Deep learning is good at finding patterns in reams of data, but can't explain how they're connected. Turing Award winner Yoshua Bengio wants to change that.