Max Hird, Florian Maire, Jeffrey Negrea. [statCO]. A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC. https://t.co/MTLGXGbyCB
@konstmish In the optimisation context you are correct, but if we take a sample X~π(-f(x))dx, the expectation of ∇f(X)∇f(X)^T is the same as the expectation of ∇^2f(X). This fact has actually been exploited in preconditioning for sampling
@konstmish That's right! See also Section 3.5 here: https://t.co/zxcZTfsetg for an analogous story in sampling, where the common misconception is that we should be preconditioning with the diagonals of the covariance.
@readalanread@BAFTA The finale was certainly embarrassing. In my view the film portrayed trauma (of architect + patron + ...) but did not give it nearly enough content. All the viewer knew was the fact of trauma, but beyond that things were basically unexplored, which was unsatisfactory.
How to use assignment problems, Sylvester's equations, permutations and projections to understand and speedup Markov chain mixing? Check out this work!
Michael C. H. Choi, Max Hird, Youjia Wang: Improving the convergence of Markov chains via permutations and projections https://t.co/cO9nrta4eb https://t.co/TKxuqBhZYA
@sp_monte_carlo I usually look at a picture of mathematicians whose names I haven't heard before. Finding Frigyes Riesz's picture on his wiki was like a jumpscare.