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cs.DS2024
Parallel Simulation for Log-concave Sampling and Score-based Diffusion Models
Huanjian Zhou, Masashi Sugiyama
Sampling from high-dimensional probability distributions is fundamental in machine learning and statistics. As datasets grow larger, computational efficiency becomes increasingly i…
cs.DS2024
The adaptive complexity of parallelized log-concave sampling
Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
In large-data applications, such as the inference process of diffusion models, it is desirable to design sampling algorithms with a high degree of parallelization. In this work, we…