Stochastic Deterministic Algorithm
![Deterministic vs. stochastic system [11] | Download Scientific Diagram](https://www.researchgate.net/profile/John-Surdu/publication/239665929/figure/fig1/AS:468163696566272@1488630331085/Deterministic-vs-stochastic-system-11.png)
![Deterministic vs. stochastic system [11] | Download Scientific Diagram](https://www.researchgate.net/profile/John-Surdu/publication/239665929/figure/fig1/AS:468163696566272@1488630331085/Deterministic-vs-stochastic-system-11_Q320.jpg)
%20to%20sample%20from%20target%20distributions%20of%20interest.%20PDMPs%20are%20non-reversible%20continuous-time%20processes%20endowed%20with%20momentum%2C%20and%20hence%20can%20mix%20better%20than%20standard%20reversible%20MCMC%20samplers.%20Furthermore%2C%20they%20can%20incorporate%20exact%20sub-sampling%20schemes%20which%20only%20require%20access%20to%20a%20single%20(randomly%20selected)%20data%20point%20at%20each%20iteration%2C%20yet%20without%20introducing%20bias%20to%20the%20algorithm's%20stationary%20distribution.%20However%2C%20the%20range%20of%20models%20for%20which%20PDMPs%20can%20be%20used%2C%20particularly%20with%20sub-sampling%2C%20is%20limited.%20We%20propose%20approximate%20simulation%20of%20PDMPs%20with%20sub-sampling%20for%20scalable%20sampling%20from%20posterior%20distributions.%20The%20approximation%20takes%20the%20form%20of%20an%20Euler%20approximation%20to%20the%20true%20PDMP%20dynamics%2C%20and%20involves%20using%20an%20estimate%20of%20the%20gradient%20of%20the%20log-posterior%20based%20on%20a%20data%20sub-sample.%20We%20thus%20call%20this%20class%20of%20algorithms%20stochastic-gradient%20PDMPs.%20Importantly%2C%20the%20trajectories%20of%20stochastic-gradient%20PDMPs%20are%20continuous%20and%20can%20leverage%20recent%20ideas%20for%20sampling%20from%20measures%20with%20continuous%20and%20atomic%20components.%20We%20show%20these%20methods%20are%20easy%20to%20implement%2C%20present%20results%20on%20their%20approximation%20error%20and%20demonstrate%20numerically%20that%20this%20class%20of%20algorithms%20has%20similar%20efficiency%20to%2C%20but%20is%20more%20robust%20than%2C%20stochastic%20gradient%20Langevin%20dynamics.)
![[PDF] Algorithms for Deterministic and Stochastic Scheduling ...](https://img.perlego.com/book-covers/3150050/9783736903036_300_450.webp)
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