Archive for Canada

likelihood inflating sampling algorithm

Posted in Books, Statistics, University life with tags , , , , , , , , on May 24, 2016 by xi'an

My friends from Toronto Radu Craiu and Jeff Rosenthal have arXived a paper along with Reihaneh Entezari on MCMC scaling for large datasets, in the spirit of Scott et al.’s (2013) consensus Monte Carlo. They devised an likelihood inflated algorithm that brings a novel perspective to the problem of large datasets. This question relates to earlier approaches like consensus Monte Carlo, but also kernel and Weierstrass subsampling, already discussed on this blog, as well as current research I am conducting with my PhD student Changye Wu. The approach by Entezari et al. is somewhat similar to consensus Monte Carlo and the other solutions in that they consider an inflated (i.e., one taken to the right power) likelihood based on a subsample, with the full sample being recovered by importance sampling. Somewhat unsurprisingly this approach leads to a less dispersed estimator than consensus Monte Carlo (Theorem 1). And the paper only draws a comparison with that sub-sampling method, rather than covering other approaches to the problem, maybe because this is the most natural connection, one approach being the k-th power of the other approach.

“…we will show that [importance sampling] is unnecessary in many instances…” (p.6)

An obvious question that stems from the approach is the call for importance sampling, since the numerator of the importance sampler involves the full likelihood which is unavailable in most instances when sub-sampled MCMC is required. I may have missed the part of the paper where the above statement is discussed, but the only realistic example discussed therein is the Bayesian regression tree (BART) of Chipman et al. (1998). Which indeed constitutes a challenging if one-dimensional example, but also one that requires delicate tuning that leads to cancelling importance weights but which may prove delicate to extrapolate to other models.

Riesling icewine

Posted in Kids, pictures, Wines with tags , , , , , , on April 20, 2016 by xi'an

postdoc grants in Canada [deadline]

Posted in Kids, Statistics, Travel, University life with tags , , , , on January 28, 2016 by xi'an

Just a reminder about the incoming deadline of January 31 for the CANSSI/INCASS postdoctoral grants. Those are restricted to members of CANSSI member institutions, though:

For the 2016-2017 year, up to two CANSSI Postdoctoral Fellowships will be awarded to suitable statistical sciences candidates working in CANSSI member institutions. Candidates should have received their PhD after March 31, 2013, and must have fulfilled all PhD requirements by the time of taking up the award.

snapshot from Montréal [and from Mont Royal]

Posted in pictures, Running, Travel with tags , , , , , on December 15, 2015 by xi'an

snapshot from Montréal [Xi’an series]

Posted in Kids, pictures, Travel with tags , , , , on December 11, 2015 by xi'an

snapshot from Montréal

Posted in pictures, Running, Travel with tags , , , , , , on December 11, 2015 by xi'an

Je reviendrai à Montréal [D-2]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , , on December 9, 2015 by xi'an

I have spent the day and more completing and compiling slides for my contrapuntal perspective on probabilistic numerics, back in Montréal, for the NIPS 2015 workshop of December 11 on this theme. As I presume the kind  invitation by the organisers was connected with my somewhat critical posts on the topic, I mostly  The day after, while I am flying back to London for the CFE (Computational and Financial Econometrics) workshop, somewhat reluctantly as there will be another NIPS workshop that day on scalable Monte Carlo.

Je veux revoir le long désert
Des rues qui n’en finissent pas
Qui vont jusqu’au bout de l’hiver
Sans qu’il y ait trace de pas


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