MCMC-algorithm Using Support Decomposition  

Oleh:

Ji, Hyunwoong ; Lee, Jaewook

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-6.
Topik: Markov-Chain Monte Carlo; Big-data; Mixing Rate; Metropolis-Hastings; Support Decompitsition
Fulltext: 1106.pdf (209.15KB)

Isi artikel

Conventional Markov-chain algorithms make use of diffusion property. Which means that new sample is recommended around the latest sample. Due to the characteristic, a lot of MCMC algorithms have a problem that their mixing rate is too low. In this paper, to overcome such problem, support decomposition is applied to previous MCMC algorithms.

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