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SUMMARY:Stereographic Barker's MCMC Proposal: Efficiency and Robustness at
  Your Disposal - Jun Yang (University of Copenhagen)
DTSTART:20241127T100500Z
DTEND:20241127T105500Z
UID:TALK221539@talks.cam.ac.uk
DESCRIPTION:We introduce a new family of robust gradient-based MCMC sample
 rs under the framework of stereographic MCMC (Yang et al. 2022) which maps
  the original high dimensional problem in Euclidean space onto a sphere. C
 ompared with the existing Stereographic Projection Sampler (SPS) which is 
 of a random-walk Metropolis type algorithm\, our new family of samplers is
  gradient-based using the Barker proposal (Livingstone and Zanella\, 2022)
 \, which improves SPS in high dimensions and is robust to tuning. Meanwhil
 e\, the proposed algorithms enjoy all the good properties of SPS\, such as
  uniform ergodicity for a large class of heavy and light-tailed distributi
 ons and "blessings of dimensionality".\nJoint work with Krzysztof Łatuszy
 ński\, Gareth O. Roberts\, and Jeffrey S. Rosenthal.
LOCATION:Seminar Room 1\, Newton Institute
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