Archive for machine learning

visualising bias and unbiasedness

Posted in Books, Kids, pictures, R, Statistics, University life with tags , , , , , , , , , on April 29, 2019 by xi'an

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) against the estimated and red distribution. While it is true that the MLE under-estimates the variance on average, the pictures are cartoonist caricatures in their deviance permanence across three replicas. When looking at 10⁵ replicas, rather than three, and at samples of size 10, rather than 2, the distinction between using the MLE (left) and the unbiased estimator of σ² (right).

When looking more specifically at the case n=2, the humongous variability of the density estimate completely dwarfs the bias issue:

Even when averaging over all 10⁵ replications, the difference is hard to spot (and both estimations are more dispersed than the truth!):

tenure track position in Clermont, Auvergne

Posted in pictures, Travel, University life with tags , , , , , , , , , , on April 23, 2019 by xi'an

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 over three years, potential tenure and titularisation at the end of a five year period, and is restricted to candidates who did their PhD or their postdoc abroad.)

Stein’s method in machine learning [workshop]

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , on April 5, 2019 by xi'an

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 probability theory for bounding the distance between probability measures using differential and difference operators. Although the method was initially designed as a technique for proving central limit theorems, it has recently caught the attention of the machine learning (ML) community and has been used for a variety of practical tasks. Recent applications include goodness-of-fit testing, generative modeling, global non-convex optimisation, variational inference, de novo sampling, constructing powerful control variates for Monte Carlo variance reduction, and measuring the quality of Markov chain Monte Carlo algorithms.

Speakers include Anima Anandkumar, Lawrence Carin, Louis Chen, Andrew Duncan, Arthur Gretton, and Susan Holmes. I am quite sorry to miss two workshops dedicated to Stein’s work in a row, the other one being at NUS, Singapore, around the Stein paradox.

position in statistics and/or machine learning at ENSAE ParisTech‐CREST

Posted in pictures, University life with tags , , , , , , , on March 28, 2019 by xi'an

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 competitive according to qualifications. The teaching duties are reduced compared to French university standards. At the time of appointment, knowledge of French is not required but it is expected that the appointee will acquire a workable knowledge of French within a reasonable time.

Candidate Profile

– PhD in Statistics or Machine Learning.
– Outstanding research, including subjects in high-dimensional statistics and machine learning.
– Publications in leading international journals in Statistics or leading outlets in Machine Learning.

Demonstrated ability to teach courses in Mathematics, Statistics and Machine Learning for engineers and to supervise projects in Applied Statistics. The successful candidate is expected to teach at least one course in mathematics, applied mathematics or introductory statistics at the undergraduate level, and one course in the “Data Science, Statistics and Machine Learning”’ specialization track during the third year of ENSAE (Master level).

Applications should submitted (in French or in English) by email to recruitment@ensae.fr :
– Curriculum vitae;
– Statement of research and teaching interests (2-4 pages);
– Names and addresses of three or more individuals willing to provide letters of reference.

Deadline for applications : April 29, 2019.
Selected candidates will be invited to present their work and project at ENSAE‐CREST.

statlearn 2019, Grenoble

Posted in Statistics with tags , , , , on March 22, 2019 by xi'an

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!

call for sessions and labs at Bay2sC0mp²⁰

Posted in pictures, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , on February 22, 2019 by xi'an

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 be selected by the scientific committee, other proposals being offered the possibility to present the associated research during a poster session [which always is a lively component of the conference]. (Conversely, we reserve the possibility of a “last call” session made from particularly exciting posters on new topics.) Plenary speakers for this conference are

and the first invited sessions are already posted on the webpage of the conference. We dearly hope to attract a wide area of research interests into a as diverse as possible program, so please accept this invitation!!!

postdoctoral position in computational statistical physics and machine learning

Posted in Statistics with tags , , , , , , , , on February 12, 2019 by xi'an