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stat.ML2025
Reheated Gradient-based Discrete Sampling for Combinatorial Optimization
Muheng Li, Ruqi Zhang
Recently, gradient-based discrete sampling has emerged as a highly efficient, general-purpose solver for various combinatorial optimization (CO) problems, achieving performance com…
stat.ML2023
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo
Ziyi Wang, Yujie Chen, Qifan Song +1
Low-precision training has emerged as a promising low-cost technique to enhance the training efficiency of deep neural networks without sacrificing much accuracy. Its Bayesian coun…