Pages that link to "Item:Q2137760"
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The following pages link to Stochastic gradient Hamiltonian Monte Carlo for non-convex learning (Q2137760):
Displaying 8 items.
- Hamiltonian Markov chain Monte Carlo for partitioned sample spaces with application to Bayesian deep neural nets (Q2131889) (← links)
- An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization (Q2159413) (← links)
- Hybrid deterministic-stochastic gradient Langevin dynamics for Bayesian learning (Q2253745) (← links)
- Nonasymptotic estimates for stochastic gradient Langevin dynamics under local conditions in nonconvex optimization (Q2682367) (← links)
- Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Nonconvex Stochastic Optimization: Nonasymptotic Performance Bounds and Momentum-Based Acceleration (Q5058053) (← links)
- Sampling can be faster than optimization (Q5218499) (← links)
- Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo (Q6134345) (← links)
- Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise (Q6155875) (← links)
