Sayak Paul

Episode 15 of the Machine Learning Street Talk (MLST) podcast, hosted by Machine Learning Street Talk (MLST), titled "Sayak Paul" was published on July 17, 2020 and runs 96 minutes.

July 17, 2020 ·96m · Machine Learning Street Talk (MLST)

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Summary

This week we spoke with Sayak Paul, who is extremely active in the machine learning community. We discussed the AI landscape in India, unsupervised representation learning, data augmentation and contrastive learning, explainability, abstract scene representations and finally pruning and the recent super positions paper. I really enjoyed this conversation and I hope you folks do too! 00:00:00 Intro to Sayak 00:17:50 AI landscape in India 00:24:20 Unsupervised representation learning 00:26:11 DATA AUGMENTATION/Contrastive learning 00:59:20 EXPLAINABILITY 01:12:10 ABSTRACT SCENE REPRESENTATIONS 01:14:50 PRUNING and super position paper

Episode Description

00:00:00 Intro to Sayak

00:17:50 AI landscape in India

00:24:20 Unsupervised representation learning

00:26:11 DATA AUGMENTATION/Contrastive learning

00:59:20 EXPLAINABILITY

01:12:10 ABSTRACT SCENE REPRESENTATIONS

01:14:50 PRUNING and super position paper

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