Tag: compressed
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A universal compression theory: Lottery ticket hypothesis and superpolynomial scaling laws
A universal compression theory: Lottery ticket hypothesis and superpolynomial scaling laws arXiv:2510.00504v1 Announce Type: new Abstract: When training large-scale models, the performance typically scales with the number of parameters and the dataset size according to a slow power law. A fundamental theoretical and practical question is whether comparable performance can be achieved with significantly smaller…
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Diffusion Generative Models Meet Compressed Sensing, with Applications to Image Data and Financial Time Series
Diffusion Generative Models Meet Compressed Sensing, with Applications to Image Data and Financial Time Series arXiv:2509.03898v1 Announce Type: new Abstract: This paper develops dimension reduction techniques for accelerating diffusion model inference in the context of synthetic data generation. The idea is to integrate compressed sensing into diffusion models: (i) compress the data into a latent…