🔻Recent Advances for a Better Understanding of Deep Learning
🖊By Arthur Pesah.
A summary of the newest deep learning trends, including Non Convex Optimization, Over-parametrization and Generalization, Generative Models, Stochastic Gradient Descent (SGD) and more.
🔹Current areas of deep learning theory research, by dividing them into four branches:
1. Non Convex Optimization
2. Overparametrization and Generalization
3. Role of Depth
4. Generative Models
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2018/10/recent-advances-deep-learning.html
#deeplearning #flatminima
#linearnetworks #optimization
#SGD #neuralnetworks
#machinelearning
🖊By Arthur Pesah.
A summary of the newest deep learning trends, including Non Convex Optimization, Over-parametrization and Generalization, Generative Models, Stochastic Gradient Descent (SGD) and more.
🔹Current areas of deep learning theory research, by dividing them into four branches:
1. Non Convex Optimization
2. Overparametrization and Generalization
3. Role of Depth
4. Generative Models
——————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2018/10/recent-advances-deep-learning.html
#deeplearning #flatminima
#linearnetworks #optimization
#SGD #neuralnetworks
#machinelearning