This is our latest selection of worldwide publications and patents in english on Examples of Fast Fourier Transform (FFT), between many scientific online journals, classified and focused on fast fourier, FFT, discrete fourier and Cooley–Tukey.
Patents: no recent patent on this particular topic. Please try the extensive manual search in the Patents Database linked just above.
Automatic Configuration Search for Parameter-Efficient Fine-Tuning
Published on 2024-05-25 by Han Zhou, Xingchen Wan, Ivan Vuli?, Anna Korhonen @MIT
Abstract: Large pretrained language models are widely used in downstream NLP tasks via task-specific fine-tuning, but such procedures can be costly. Recently, Parameter-Efficient Fine-Tuning (PEFT) methods have achieved strong task performance while updating much fewer parameters than full model fine-tuning (FFT). However, it is non-trivial to make informed design choices on the PEFT configurations, such as their architecture, the number of tunable parameters, and even the layers in which the PEFT modules[...]
Our summary: Efficient fine-tuning method achieved with fewer parameters. AutoPEFT uses Bayesian optimization to discover optimal configurations. Outperforms existing methods on GLUE and SuperGLUE tasks. Pareto-optimal set balances performance and cost.
automatic configuration search, parameter-efficient fine-tuning, neural architecture search, pretrained language models, task-specific fine-tuning
Publication
Anyone else amazed at how FFT is revolutionizing tech? But how accessible will this be for smaller startups?
Interesting read! But isnt the radix-2 Cooley-Tukey FFT algorithm more efficient than the mixed-radix algorithm mentioned here? Curious to know your take.
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