3 papers
cs.LG2026
Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling
Yu Yao, Huanjian Zhou, Andi Han +2
Discrete diffusion models are widely used for learning and generating discrete distributions. As the generation process is inherently sequential, the acceleration of sampling is of…
math.OC2025
The Adaptive Complexity of Finding a Stationary Point
Huanjian Zhou, Andi Han, Akiko Takeda +1
In large-scale applications, such as machine learning, it is desirable to design non-convex optimization algorithms with a high degree of parallelization. In this work, we study th…
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…