[Adapt] FW: probabilistic-programming Digest, Vol 14, Issue 5

Kenny Zhu kzhu at cs.sjtu.edu.cn
Fri Oct 31 09:31:26 CST 2014

Check this out please.



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Date: Thu, Oct 30, 2014 at 9:00 AM
Subject: probabilistic-programming Digest, Vol 14, Issue 5
To: probabilistic-programming at lists.csail.mit.edu

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Today's Topics:

   1. Announcing: The Design and Implementation of Probabilistic
      Programming Languages (dippl.org) (Noah Goodman)
   2. Reminder: CALL FOR CONTRIBUTIONS --- 3rd NIPS Workshop on
      Probabilistic Programming (Daniel Roy)


Message: 1
Date: Wed, 29 Oct 2014 10:37:53 -0700
From: Noah Goodman <ngoodman at stanford.edu>
To: probabilistic-programming at lists.csail.mit.edu
Cc: Andreas Stuhlm?ller <andreas at stuhlmueller.org>
Subject: [Probabilistic-programming] Announcing: The Design and
        Implementation of Probabilistic Programming Languages (dippl.org)
        <CAPLvLdA8uNw5R6sE9wEQpkgVojXQGC+V8KQ_qny9mKf2-FY96w at mail.gmail.com <mailto:CAPLvLdA8uNw5R6sE9wEQpkgVojXQGC%2BV8KQ_qny9mKf2-FY96w at mail.gmail.com> >
Content-Type: text/plain; charset="utf-8"

Hello friends and colleagues,

We have written a set of online notes on The Design and Implementation of
Probabilistic Programming Languages <http://dippl.org/> (it's up at

We attempt to give easy-to-follow description of lightweight
implementations for enumeration, particle filtering, and Metropolis
Hastings. The result is a fun little PPL based on javascript: WebPPL,
available on github and linked from the notes.

These notes are still preliminary and rough in places; we'd welcome your
comments and input (and especially pull-requests).


-Noah and Andreas
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Message: 2
Date: Wed, 29 Oct 2014 15:12:56 -0400
From: Daniel Roy <droy at utstat.toronto.edu>
To: probabilistic-programming
        <probabilistic-programming at lists.csail.mit.edu>
Subject: [Probabilistic-programming] Reminder: CALL FOR CONTRIBUTIONS
        --- 3rd NIPS Workshop on Probabilistic Programming
        <CAAgJ5Oq1qB3MC-KKavZZ9UGt849ga_Er-zML+B4MFcGBb0Hb1g at mail.gmail.com <mailto:CAAgJ5Oq1qB3MC-KKavZZ9UGt849ga_Er-zML%2BB4MFcGBb0Hb1g at mail.gmail.com> >
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Hello PPL community:

We are now accepting early submissions to the Probabilistic Programming
Workshop for those needing early decisions.  Note that NIPS has a November
7 early registration deadline.  We've also simplified the submission
requirements for languages/systems and problem descriptions, so please have
a look over those.

Finally, please consider pre-registering



CALL FOR CONTRIBUTIONS --- 3rd NIPS Workshop on Probabilistic Programming


Vikash Mansinghka, Dan Roy, Stuart Russell, Tom Dietterich, Josh Tenenbaum


----- OCT 24 : Accepting submissions (for early decisions see ^^ below)
----- NOV 07 : Extended abstracts due (and NIPS early registration
----- NOV 10 : Notification of acceptance
----- DEC 13 : Workshop

^^ On request, decisions for submissions received between October 24 and
November 3 will be made within 72 hours, to facilitate travel planning and
early registration.




Probabilistic models and approximate inference algorithms have become
widely-used tools, central to fields ranging from cosmology to robotics to
genetics. However, even simple variations on models and algorithms from the
standard machine learning and statistics toolkits can be difficult and
time-consuming to design, specify, analyze, implement, optimize and debug.
Due to these challenges, integrated, fully probabilistic approaches to
fundamental AI problems can be impractical. Probabilistic programming aims
to address these challenges by developing formal languages and software
systems that integrate key ideas from probabilistic modeling and inference
with programming languages and Turing-universal computation.

The field of probabilistic programming has seen rapid growth and progress
over the last two years. Several languages and open-source implementations
are now mature enough to support real-world applications, especially in
data analysis. Many new probabilistic programming languages have been
developed; most of these are domain-specific, but some aim to be
general-purpose. Formal connections to computable analysis, measure theory,
and computational complexity are emerging, along with new AI architectures
that make use of the representational flexibility that probabilistic
programs and probabilistic programming systems provide. New problems have
also emerged. There is a widespread need for software tools that implement
mathematically rigorous approaches to profiling, testing, verifying and
debugging probabilistic programs, and for high-quality libraries of models
and inference techniques.

The 3rd NIPS Workshop on Probabilistic Programming will survey recent
progress, including results from the ongoing DARPA PPAML program. A key
theme will be articulating formal connections between probabilistic
programming and other fields central to the NIPS community.


We are seeking three types of extended abstract submissions:

1. RESEARCH ABSTRACTS --- Original research in probabilistic programming
methodology and/or its applications. All aspects of probabilistic
programming are appropriate, including theory, language design, inference,
systems considerations, and applications.

2. LANGUAGE/SYSTEM DESCRIPTIONS --- Descriptions of languages and systems
under active research and development. Abstracts should explain the
intended coverage in terms of the models, datasets, queries, inference
strategies and representative applications that are supported by the
language. Distinctive features of the language design and system
architecture are also of interest. All abstracts must include code and
example outputs for at least two probabilistic programs.

3. CHALLENGE PROBLEMS --- Suggestions for challenge problems that the
probabilistic programming community should consider. Application
suggestions should introduce the problem, link to publicly available domain
knowledge and/or data, suggest relevant modeling idioms and inference
strategies, describe the current state-of-the-art, and characterize the
potential impact if the problem is solved (ideally given multiple
quantitatively specified levels of computational and inferential
performance). Descriptions of fundamental research challenges that have
arisen or are likely to arise are also of interest, especially if the
challenge and/or the likely solutions involve connections to other fields.

Submissions should sent by email to

     probprog2014 at gmail.REMOVE.com

In order to aid processing, the email subject line should contain the word
"submission", as well as the following keywords:

-- "research", "description", or "challenge" based on the type of
-- "talk", if and only if the authors would like the abstract
    considered for a contributed talk in addition to a poster; and
-- ?early decision?, if and only if the authors need to hear back
    within 72 hours concerning acceptance for registration/planning

The body of the email should include

-- a title,
-- a list of authors and emails, and
-- a PDF attachment in the NIPS LaTeX style.

Submissions should be ~3 pages + references, and they will be reviewed for
correctness, clarity, relevance, and, in the case of research submissions,
novelty. An optional questionnaire URL will be released in November for
Language/System and Challenge Problem submissions. Accepted contributions
will be made available shortly before the workshop, and will be linked
online with the authors? permission.

Daniel Roy

           Department of Statistical Sciences
           University of Toronto

           Department of Computer and Mathematical Sciences
           University of Toronto Scarborough

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