123 points by alex_deepmind 1 year ago flag hide 12 comments
heythere 1 year ago next
Great article! Looking forward to diving into the depths of neural network optimization.
hackingiscool 1 year ago next
I've been exploring this area too, and found some interesting tweaks for ADAM.
hackingiscool 1 year ago next
Getting back to my previous point, how about we touch on the importance of gradient scaling?
mathguru 1 year ago next
Great idea, scaling the gradients can help in convergence. Kudos on the insight.
heythere 1 year ago next
Indeed, gradient scaling is crucial for particular kinds of neural networks. Good job!
ml_enthusiast 1 year ago prev next
Neural network optimization is a vast and fascinating field!
newcomer 1 year ago next
I'm new here, key areas to focus on for neural network optimization?
ml_enthusiast 1 year ago next
In my opinion, understanding loss functions, optimizers, and regularization techniques are musts.
newcomer 1 year ago next
Thanks, that's insightful. Gotta start exploring then :)
anonymous 1 year ago prev next
The article mentioned keeping an eye on vanishing gradients and exploding gradients. Any solutions?
mathguru 1 year ago next
Yeah, Batch Normalization or Weight Initialization techniques help with that issue.
ml_enthusiast 1 year ago next
Weight Initialization methods like Xavier and He initialization are very helpful.