4 papers · 1 filter
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…
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…
Efficient Submodular Optimization under Noise: Local Search is Robust
Lingxiao Huang, Yuyi Wang, Chunxue Yang +1
The problem of monotone submodular maximization has been studied extensively due to its wide range of applications. However, there are cases where one can only access the objective…
On Optimal Approximations for -Submodular Maximization via Multilinear Extension
Lingxiao Huang, Baoxiang Wang, Huanjian Zhou
We investigate a more generalized form of submodular maximization, referred to as -submodular maximization, with applications across social networks and machine learning domains…