Cover Image

Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Neufeld, Ariel, Zhang, Ying
Format:	Preprint
Published:	2024
Subjects:	Statistics Theory Probability Computation Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Non-asymptotic analysis of Langevin-type Monte Carlo algorithms
by: Nakakita, Shogo
Published: (2023)

Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting
by: Neufeld, Ariel, et al.
Published: (2022)

Parallelized Midpoint Randomization for Langevin Monte Carlo
by: Yu, Lu, et al.
Published: (2024)

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
by: Dalalyan, Arnak S., et al.
Published: (2017)

Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
by: Miranda, Charles, et al.
Published: (2023)

Non-asymptotic Analysis of Poisson randomized midpoint Langevin Monte Carlo
by: Shen, Tian, et al.
Published: (2025)

Convergence of Kinetic Langevin Monte Carlo on Lie groups
by: Kong, Lingkai, et al.
Published: (2024)

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients
by: Lytras, Iosif, et al.
Published: (2025)

Sampling and estimation on manifolds using the Langevin diffusion
by: Bharath, Karthik, et al.
Published: (2023)

Efficient Sampling on Riemannian Manifolds via Langevin MCMC
by: Cheng, Xiang, et al.
Published: (2024)

Complexity of Markov Chain Monte Carlo for Generalized Linear Models
by: Chak, Martin, et al.
Published: (2025)

Time-Inhomogeneous Preconditioned Langevin Dynamics
by: Falk, Alexander, et al.
Published: (2026)

Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks
by: Liang, Luxu, et al.
Published: (2024)

Tail-Sensitive KL and Rényi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings
by: Bou-Rabee, Nawaf, et al.
Published: (2026)

Sampling from multimodal distributions with warm starts: Non-asymptotic bounds for the Reweighted Annealed Leap-Point Sampler
by: Lee, Holden, et al.
Published: (2025)

On the convergence of dynamic implementations of Hamiltonian Monte Carlo and No U-Turn Samplers
by: Durmus, Alain, et al.
Published: (2023)

Non-asymptotic Analysis of Diffusion Annealed Langevin Monte Carlo for Generative Modelling
by: Cordero-Encinar, Paula, et al.
Published: (2025)

Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
by: Ghosh, Soumyadip, et al.
Published: (2021)

Sampling conditioned diffusions via Pathspace Projected Monte Carlo
by: Grafke, Tobias
Published: (2025)

Concentration of the Langevin Algorithm's Stationary Distribution
by: Altschuler, Jason M., et al.
Published: (2022)

Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
by: Guo, Wei, et al.
Published: (2024)

Convergence Bounds for Sequential Monte Carlo on Multimodal Distributions using Soft Decomposition
by: Lee, Holden, et al.
Published: (2024)

High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
by: Liang, Tengyuan, et al.
Published: (2022)

Convergence rate of randomized midpoint Langevin Monte Carlo
by: Li, Ruinan, et al.
Published: (2025)

A calculus for Markov chain Monte Carlo: studying approximations in algorithms
by: Caprio, Rocco, et al.
Published: (2023)

A Dynamical System View of Langevin-Based Non-Convex Sampling
by: Karimi, Mohammad Reza, et al.
Published: (2022)

Sharp bounds on aggregate expert error
by: Kontorovich, Aryeh, et al.
Published: (2024)

Sliding down the stairs: how correlated latent variables accelerate learning with neural networks
by: Bardone, Lorenzo, et al.
Published: (2024)

Dimension-free error estimate for diffusion model and optimal scheduling
by: de Bortoli, Valentin, et al.
Published: (2025)

Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev
by: Chewi, Sinho, et al.
Published: (2021)

Improved Guarantees for Langevin Monte Carlo with Average Smoothness
by: Dalalyan, Arnak S., et al.
Published: (2026)

Regime-Switching Langevin Monte Carlo Algorithms
by: Wang, Xiaoyu, et al.
Published: (2025)

Finite sample bounds for barycenter estimation in geodesic spaces
by: Brunel, Victor-Emmanuel, et al.
Published: (2025)

Analysis of a multi-target linear shrinkage covariance estimator
by: Oriol, Benoit
Published: (2024)

On the distance between mean and geometric median in high dimensions
by: Schwank, Richard, et al.
Published: (2025)

The high-dimensional asymptotics of first order methods with random data
by: Celentano, Michael, et al.
Published: (2021)

Universality of high-dimensional scaling limits of stochastic gradient descent
by: Gheissari, Reza, et al.
Published: (2025)

Bayesian Inference with Shaped Deep Non-linear MLPs
by: Hanin, Boris, et al.
Published: (2026)

MetaCURL: Non-stationary Concave Utility Reinforcement Learning
by: Moreno, Bianca Marin, et al.
Published: (2024)

Non-Asymptotic Analysis of Data Augmentation for Precision Matrix Estimation
by: Morisset, Lucas, et al.
Published: (2025)