contrastive-learning

[top, cut off] "...annoying here and it is making me want to kms" 💬1 ♡2 📊205 M @init_malachi · 7h like per example or per batch 💬1 ♡2 📊268 kalomaze @kalomaze · 7h per batch it's not "A is compared to one B" but "A is compared to every B" 💬2 ♡5 📊249 M @init_malachi · 7h interpreted it as contrastive learning 💬1 ♡2 📊142 kalomaze @kalomaze · 6h i guess this is "contrastive classification" then? 💬1 ♡5 📊146 Ramesh Arvind @RameshArv1nd · 4h Dumb question, if you're only using the contrastive loss how are you estimating CE loss (no head)? And also why abandon CE and not add the contrastive term as an aux loss. I imagine for binary you could get away with some min/max sigmoidal diff across the batch [cut off]