Other methods and algorithms can be used, and their complexity still place them in the modern definition of machine learning. Not All Optimization Is Local, But Enough Is To Matter ...

Say goodbye to hours of tuning hyperparameters! University of Tokyo researchers introduce ADOPT, a groundbreaking optimizer that stabilizes deep learning training across diverse applications ...

In addition to pure deep neural networks (DNNs), sometimes people use hybrid vision models, which combine deep learning with classical machine learning algorithms that perform specific sub-tasks.

Since 2012, “deep learning” has mostly meant using back-propagation to optimize all the parameters in a deep computational graph representing some differentiable function.

Algorithms and deep learning: the best of both worlds. Veličković was in many ways the person who kickstarted the algorithmic reasoning direction in DeepMind.

Using a range of real datasets and basic Python libraries for data manipulation, vector/matrix algebra, and automatic differentiation students will code up - from scratch - fundamental optimization ...

With all the excitement over neural networks and deep-learning techniques, it’s easy to imagine that the world of computer science consists of little else. Neural networks, after all, have begun ...

For the algorithm training, the participating teams had access to a large annotated PET/CT dataset. All algorithms submitted for the final phase of the competition are based on deep learning methods.