Daniel Shalam
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View article: Unsupervised Representation Learning by Balanced Self Attention Matching
Unsupervised Representation Learning by Balanced Self Attention Matching Open
Many leading self-supervised methods for unsupervised representation learning, in particular those for embedding image features, are built on variants of the instance discrimination task, whose optimization is known to be prone to instabil…
View article: The Balanced-Pairwise-Affinities Feature Transform
The Balanced-Pairwise-Affinities Feature Transform Open
The Balanced-Pairwise-Affinities (BPA) feature transform is designed to upgrade the features of a set of input items to facilitate downstream matching or grouping related tasks. The transformed set encodes a rich representation of high ord…
View article: The Self-Optimal-Transport Feature Transform
The Self-Optimal-Transport Feature Transform Open
The Self-Optimal-Transport (SOT) feature transform is designed to upgrade the set of features of a data instance to facilitate downstream matching or grouping related tasks. The transformed set encodes a rich representation of high order r…