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Re: [802SEC] FW: [UAI] letter of resignation from Machine Learning journal (fw d)

John -

I can only agree with your comments.  This (or similar) is the publication 
model that I would like to see adopted by the IEEE, and adopting it right 
now would not be any too soon, in my opinion.

Athough the "Get IEEE 802" programme is a considerable advance on where we 
were hitherto, it really doesn't make it when compared with where we need 
to be.


At 12:01 09/10/2001 -0400, Montague, John E wrote:

>Dear Colleagues:
>This is forwarded for your information.  I urge you to consider and promote
>the JMLR model as an intellectual property approach for the IEEE-SA, the
>IEEE, and all its affiliated societies.  What makes this so attractive?
>-- rapid on-line availability to everyone at no cost
>-- timely hard copy available for those who need it
>-- IEEE entities retain sponsorship credit, quality control, and resulting
>industry leadership image
>-- IEEE continues to be the "first print publisher"
>-- authors (the entire committee voting membership, individual and
>institutional) retain rights to their work
>The JMLR model, or something like it, is the way of the future for all
>technical literature.  Failure by the IEEE (and ACM, and ...) to do
>something similar will likely result in a repetition of the scenario below.
>John Montague
>---------- Forwarded message ----------
>Date:   Mon, 08 Oct 2001 16:28:26 -0700
>From:   Michael Jordan <>
>To:     "" <>
>Subject:        [UAI] letter of resignation from Machine Learning journal
>Dear colleagues in machine learning,
>The forty people whose names appear below have resigned from the Editorial
>Board of the Machine Learning Journal (MLJ).  We would like to make our
>resignations public, to explain the rationale for our action, and to
>indicate some of the implications that we see for members of the machine
>learning community worldwide.
>The machine learning community has come of age during a period of enormous
>change in the way that research publications are circulated.  Fifteen years
>ago research papers did not circulate easily, and as with other research
>communities we were fortunate that a viable commercial publishing model was
>in place so that the fledgling MLJ could begin to circulate.  The needs of
>the community, principally those of seeing our published papers circulate as
>widely and rapidly as possible, and the business model of commercial
>publishers were in harmony.
>Times have changed.  Articles now circulate easily via the Internet, but
>unfortunately MLJ publications are under restricted access.  Universities
>and research centers can pay a yearly fee of $1050 US to obtain unrestricted
>access to MLJ articles (and individuals can pay $120 US).  While these fees
>provide access for institutions and individuals who can afford them, we feel
>that they also have the effect of limiting contact between the current
>machine learning community and the potentially much larger community of
>researchers worldwide whose participation in our field should be the fruit
>of the modern Internet.
>None of the revenue stream from the journal makes its way back to authors,
>and in this context authors should expect a particularly favorable return on
>their intellectual contribution---they should expect a service that
>maximizes the distribution of their work.  We see little benefit accruing to
>our community from a mechanism that ensures revenue for a third party by
>restricting the communication channel between authors and readers.
>In the spring of 2000, a new journal, the Journal of Machine Learning
>Research (JMLR), was created, based on a new vision of the journal
>publication process in which the editorial board and authors retain
>significant control over the journal's content and distribution.  Articles
>published in JMLR are available freely, without limits and without
>conditions, at the journal's website,  The content and
>format of the website are entirely controlled by the editorial board, which
>also serves its traditional function of ensuring rigorous peer review of
>journal articles.  Finally, the journal is also published in a hardcopy
>version by MIT Press.
>Authors retain the copyright for the articles that they publish in JMLR.
>The following paragraph is taken from the agreement that every author signs
>with JMLR (see
>You [the author] retain copyright to your article, subject only to the
>specific rights given to MIT Press and to the Sponsor [the editorial board]
>in the following paragraphs.  By retaining your copyright, you are reserving
>for yourself among other things unlimited rights of electronic distribution,
>and the right to license your work to other publishers, once the article has
>been published in JMLR by MIT Press and the Sponsor [the editorial board].
>After first publication, your only obligation is to ensure that appropriate
>first publication credit is given to JMLR and MIT Press.
>We think that many will agree that this is an agreement that is reflective
>of the modern Internet, and is appealing in its recognition of the rights of
>authors to distribute their work as widely as possible.  In particular,
>authors can leave copies of their JMLR articles on their own homepage.
>Over the years the editorial board of MLJ has expanded to encompass all of
>the various perspectives on the machine learning field, and the editorial
>board's efforts in this regard have contributed greatly to the sense of
>intellectual unity and community that many of us feel.  We believe, however,
>that there is much more to achieve, and that our further growth and further
>impact will be enormously enhanced if via our flagship journal we are able
>to communicate more freely, easily, and universally.
>Our action is not unprecedented.  As documented at the Scholarly Publishing
>and Academic Resources Coalition (SPARC) website,,
>there are many areas in science where researchers are moving to low-cost
>publication alternatives.  One salient example is the case of the journal
>"Logic Programming".  In 1999, the editors and editorial advisors of this
>journal resigned to join "Theory and Practice of Logic Programming", a
>Cambridge University Press journal that encourages electronic dissemination
>of papers.
>In summary, our resignation from the editorial board of MLJ reflects our
>belief that journals should principally serve the needs of the intellectual
>community, in particular by providing the immediate and universal access to
>journal articles that modern technology supports, and doing so at a cost
>that excludes no one.  We are excited about JMLR, which provides this access
>and does so unconditionally.  We feel that JMLR provides an ideal vehicle to
>support the near-term and long-term evolution of the field of machine
>learning and to serve as the flagship journal for the field.  We invite all
>of the members of the community to submit their articles to the journal and
>to contribute actively to its growth.
>Sincerely yours,
>Chris Atkeson
>Peter Bartlett
>Andrew Barto
>Jonathan Baxter
>Yoshua Bengio
>Kristin Bennett
>Chris Bishop
>Justin Boyan
>Carla Brodley
>Claire Cardie
>William Cohen
>Peter Dayan
>Tom Dietterich
>Jerome Friedman
>Nir Friedman
>Zoubin Ghahramani
>David Heckerman
>Geoffrey Hinton
>Haym Hirsh
>Tommi Jaakkola
>Michael Jordan
>Leslie Kaelbling
>Daphne Koller
>John Lafferty
>Sridhar Mahadevan
>Marina Meila
>Andrew McCallum
>Tom Mitchell
>Stuart Russell
>Lawrence Saul
>Bernhard Schoelkopf
>John Shawe-Taylor
>Yoram Singer
>Satinder Singh
>Padhraic Smyth
>Richard Sutton
>Sebastian Thrun
>Manfred Warmuth
>Chris Williams
>Robert Williamson