Non-Asymptotic Estimates for Stochastic Gradient Hamiltonian Monte Carlo Algorithm with Dependent Data Streams

Author:

杨 金圆

Publisher

Hans Publishers

Reference15 articles.

1. Raginsky, M., Rakhlin, A. and Telgarsky, M. (2017) Non-Convex Learning via Stochastic Gradient Langevin Dynamics: A Nonasymptotic Analysis. Conference on Learning Theory, 65, 1674-1703.

2. Laplace's Method Revisited: Weak Convergence of Probability Measures

3. Diffusion for Global Optimization in $\mathbb{R}^n $

4. Welling, M. and Teh, Y.W. (2011) Bayesian Learning via Stochastic Gradient Langevin Dynamics. Proceedings of the 28th International Conference on Machine Learning (ICML-11), Bellevue, Washington, 28 June 2011, 681-688.

5. Chen, T., Fox, E. and Guestrin, C. (2014) Stochastic Gradient Hamiltonian Monte Carlo. International Conference on Machine Learning, Bejing, 22-24 June 2014, 1683-1691.

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