UC Berkeley Researchers Propose CRATE: A Novel White-Box Transformer for Efficient Data Compression and Sparsification in Deep Learning

The practical success of deep learning in processing and modeling large amounts of high-dimensional and multi-modal data has grown exponentially in recent years. Much of this achievement can be attributed to deep networks’ skill at discovering compressible low-dimensional structures in data and subsequently transforming these discoveries into an economical, i.e., compact and structured, representation. Such […]

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