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Stanley J. Osher

2 accepted papers

2023

A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys

ICASSP 2023accepted

Pairwise dot product-based self-attention is key to the success of transformers which achieve state-of-the-art performance across a variety of applications in language and vision, but are costly to compute. It has been shown that most attention scores and keys in transformers are redundant and can b…

Cited by 0SourceScholar
2017

Pre-processing and classification of hyperspectral imagery via selective inpainting

ICASSP 2017accepted

We propose a semi-supervised algorithm for processing and classification of hyperspectral imagery. For initialization, we keep 20% of the data intact, and use Principal Component Analysis to discard voxels from noisier bands and pixels. Then, we use either an Accelerated Proximal Gradient algorithm…

Cited by 0SourceScholar