Archive for corrigendum

Nature snapshots [and snide shots]

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on October 12, 2017 by xi'an

A very rich issue of Nature I received [late] just before leaving for Warwick with a series of reviews on quantum computing, presenting machine learning as the most like immediate application of this new type of computing. Also including irate letters and an embarassed correction of an editorial published the week before reflecting on the need (or lack thereof) to remove or augment statues of scientists whose methods were unethical, even when eventually producing long lasting advances. (Like the 19th Century gynecologist J. Marion Sims experimenting on female slaves.) And a review of a book on the fascinating topic of Chinese typewriters. And this picture above of a flooded playground that looks like a piece of abstract art thanks to the muddy background.

“Quantum mechanics is well known to produce atypical patterns in data. Classical machine learning methods such as deep neural networks frequently have the feature that they can both recognize statistical patterns in data and produce data that possess the same statistical patterns: they recognize the patterns that they produce. This observation suggests the following hope. If small quantum information processors can produce statistical patterns that are computationally difficult for a classical computer to produce, then perhaps they can also recognize patterns that are equally difficult to recognize classically.” Jacob Biamonte et al., Nature, 14 Sept 2017

One of the review papers on quantum computing is about quantum machine learning. Although like Jon Snow I know nothing about this, I find it rather dull as it spends most of its space on explaining existing methods like PCA and support vector machines. Rather than exploring potential paradigm shifts offered by the exotic nature of quantum computing. Like moving to Bayesian logic that mimics a whole posterior rather than produces estimates or model probabilities. And away from linear representations. (The paper mentions a O(√N) speedup for Bayesian inference in a table, but does not tell more, which may thus be only about MAP estimators for all I know.) I also disagree with the brave new World tone of the above quote or misunderstand its meaning. Since atypical and statistical cannot but clash, “universal deep quantum learners may recognize and classify patterns that classical computers cannot” does not have a proper meaning. The paper contains a vignette about quantum Boltzman machines that finds a minimum entropy approximation to a four state distribution, with comments that seem to indicate an ability to simulate from this system.

ABC for parameter inference and model selection in dynamical systems (2)

Posted in Statistics with tags , , , , on January 8, 2009 by xi'an

As it happens, I did not get the final and published version of the paper “Approximate Bayesian Computation scheme for parameter inference and model selection in dynamical systems” by Toni, Welch, Strelkowa, Ipsen and Stumpf, as of June 12, but an earlier version of April 31, 2008, where there was a typo. In the final version, the difficulty I had yesterday has vanished in that the importance weight used in the ABC SMC algorithm is now correct (and corresponds to the ABC PMC weight as well). There are a few minor points of contention remaining with the appendix A of the paper, in particular in the definition of ηt around (A3) but the algorithm stands corrected. Sorry if this created any confusion!

Ps-I did not even know the Journal of the Royal Society Interface existed, as it is not an usual outlet for Statistics papers… It appears to be an equivalent to the US PNAS (and in a more remote manner to the French Notes aux Comptes Rendus de l’Académie des Sciences). To end up on a light note, the current news heading on the Royal Society webpage is “Fluorescent mice help shed light on the spread of a dangerous disease“. Of course! The more fluorescent, the more light!

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