New insights into training dynamics of deep classifiers
MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.
MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
A new tool brings the benefits of AI programming to a much broader class of problems.