Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Oren Mangoubi, Nisheeth Vishnoi
–Neural Information Processing Systems
Hamiltonian Monte Carlo (HMC) is a widely deployed method to sample from highdimensional distributions in Statistics and Machine learning. HMC is known to run very efficiently in practice and its popular second-order "leapfrog" implementation has long been conjectured to run in d
Neural Information Processing Systems
Mar-27-2025, 02:46:29 GMT