A question on X validated led me to wonder at the point made by Christopher Bishop in his Pattern Recognition and Machine Learning book about the MLE of the Normal variance being biased. As it is illustrated by the above graph that opposes the true and green distribution of the data (made of two points) […]
Category: machine learning
tenure track position in Clermont, Auvergne
My friend Arnaud Guillin pointed out this opening of a tenure-track professor position at his University of Clermont Auvergne, in Central France. With specialty in statistics and machine-learning, especially deep learning. The deadline for applications is 12 May 2019. (Tenure-track positions are quite rare in French universities and this offer includes a limited teaching load […]
Stein’s method in machine learning [workshop]
There will be an ICML workshop on Stein’s method in machine learning & statistics, next July 14 or 15, located in Long Beach, CA. Organised by François-Xavier Briol (formerly Warwick), Lester Mckey, Chris Oates (formerly Warwick), Qiang Liu, and Larry Golstein. To quote from the webpage of the workshop Stein’s method is a technique from […]
Stein’s method in machine learning [workshop]
There will be an ICML workshop on Stein’s method in machine learning & statistics, next July 14 or 15, located in Long Beach, CA. Organised by François-Xavier Briol (formerly Warwick), Lester Mckey, Chris Oates (formerly Warwick), Qiang Liu, and Larry Golstein. To quote from the webpage of the workshop Stein’s method is a technique from […]
position in statistics and/or machine learning at ENSAE ParisTech‐CREST
ENSAE ParisTech and CREST are currently inviting applications for a position of Assistant or Associate Professor in Statistics or Machine Learning. The appointment starts in September, 2019, at the earliest. At the level of Assistant Professor, the position is for an initial three-year term renewable for another three years before the tenure evaluation. Salary is […]
statlearn 2019, Grenoble
In case you are near the French Alps next week, STATLEARN 2019 will take place in Grenoble, the week after next, 04 and 05 April. The program is quite exciting, registration is free of charge!, and still open, plus the mountains are next door!
Gartner’s 2019 Take on Data Science Software
I’ve just updated The Popularity of Data Science Software to reflect my take on Gartner’s 2019 report, Magic Quadrant for Data Science and Machine Learning Platforms. To save you the trouble of digging through all 40+ pages of my report, here’s just the updated section: Continue reading →
call for sessions and labs at Bay2sC0mp²⁰
A call to all potential participants to the incoming BayesComp 2020 conference at the University of Florida in Gainesville, Florida, 7-10 January 2020, to submit proposals [to me] for contributed sessions on everything computational or training labs [to David Rossell] on a specific language or software. The deadline is April 1 and the sessions will […]
postdoctoral position in computational statistical physics and machine learning
the $1,547.02 book on neural networks
prepaid ABC
Merijn Mestdagha, Stijn Verdoncka, Kristof Meersa, Tim Loossensa, and Francis Tuerlinckx from the KU Leuven, some of whom I met during a visit to its Wallon counterpart Louvain-La-Neuve, proposed and arXived a new likelihood-free approach based on saving simulations on a large scale for future users. Future users interested in the same model. The very […]
Nature Outlook on AI
The 29 November 2018 issue of Nature had a series of papers on AIs (in its Outlook section). At the general public (awareness) level than in-depth machine-learning article. Including one on the forecasted consequences of ever-growing automation on jobs, quoting from a 2013 paper by Carl Frey and Michael Osborne [of probabilistic numerics fame!] that […]