New journal: Mathematical Statistics and Learning

I am thrilled to announce the launch of a new journal, “Mathematical Statistics and Learning”, to be edited be the European Mathematical Society. The goal of the journal is be the natural home for the top works addressing the mathematical challenges that arise from the current data revolution (as well as breakthroughs on classical data analysis problems!). I personally wish such a journal had existed for at least a decade and I am very happy to be part of this endeavor as an associate editor. Please consider submitting your very best mathematical work in statistics and learning to this journal!

Some more details provided by Gabor Lugosi and Shahar Mendelson on behalf of the Editorial Board:

The journal is devoted to research articles of the highest quality in all aspects of Mathematical Statistics and Learning, including those studied in traditional areas of Statistics and in Machine Learning as well as in Theoretical Computer Science and Signal Processing. We believe that at this point in time there is no venue for top level mathematical publications in those areas, and our aim is to make the new journal such a venue.

The journal’s Editorial Board consists of the Editors,

Luc Devroye (McGill),

Gabor Lugosi (UPF Barcelona),

Shahar Mendelson (Technion and ANU),

Elchanan Mossel (MIT),

Mike Steele (U. Pennsylvania),

Alexandre Tsybakov (ENSAE),

Roman Vershynin (U. Michigan),

and the Associate Editors,

Sebastien Bubeck (Microsoft Research),

Andrea Montanari (Stanford),

Jelani Nelson (Harvard),

Philippe Rigollet (MIT),

Sara van de Geer (ETH – Zurich),

Ramon van Handel (Princeton),

Rachel Ward (UT – Austin).

The success of the journal depends entirely on our community;  we need your help and support in making it the success we believe it can be. We therefore ask that you consider submitting to the journal results you think are of a very high quality.

The first issue of the journal is scheduled to appear in early 2018.