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cs.LG2024
Cluster Specific Representation Learning
Mahalakshmi Sabanayagam, Omar Al-Dabooni, Pascal Esser
Representation learning aims to extract meaningful lower-dimensional embeddings from data, known as representations. Despite its widespread application, there is no established def…
cs.LG2024★ 1 cited
When can we Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis?
Gautham Govind Anil, Pascal Esser, Debarghya Ghoshdastidar
Contrastive learning is a paradigm for learning representations from unlabelled data that has been highly successful for image and text data. Several recent works have examined con…