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Subject:

2nd CFP - NIPS Workshop - Advances in Structured Learning for Text and Speech Processing

From:

Koby Crammer <[log in to unmask]>

Reply-To:

The Support Vector Machine discussion list <[log in to unmask]>

Date:

Wed, 26 Oct 2005 10:27:00 -0400

Content-Type:

TEXT/PLAIN

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (129 lines)

################################################################

  			CALL FOR PARTICIPATION

      Advances in Structured Learning for Text and Speech Processing

  			  a workshop at the

  	      2005 Neural Information Processing Systems
  			  (NIPS) Conference

  	   Submission deadline: Tuesday, November 1st, 2005

  	   http://www.cis.upenn.edu/~crammer/workshop-index.html


################################################################

Organizers:
-----------
Fernando Pereira	CIS, University of Pennsylvania
Michael Collins	        CSAIL, MIT
Jeff Bilmes		EE,  University of Washington
Koby Crammer		CIS, University of Pennsylvania


Overview:

This workshop is intended for researchers and students interested in
developing and applying structured classification methods to text and
speech processing problems. Recent advances in structured
classification provide promising alternatives to the probabilistic
generative models that have been the mainstay of speech recognition
and statistical language processing. However, powerful features of
probabilistic generative models, such as hidden variables and
compositional combination of several kinds of evidence, do not
transfer cleanly to all structured classification methods. Starting
with surveys of the state-of-the-art in structured classification for
text and speech, the workshop will focus on successes, failures, and
directions for improvement of structured classification methods for
text and speech and possible syntheses between the new structured
classification methods and traditional generative models. Comparison
will also be made with "generative" vs. "discriminative" training
procedures in structure classification problems. A successful workshop
will identify critical questions that current methods are not yet
capable of solving, and promising directions for solution. For
instance, we hope to achieve a better understanding of how
discriminative models may work with missing information, such as
under-specified alignments or syntactic analyses --- we plan, more
generally, answer questions such as why, when, and where use a
generative model. Such problems arise in both speech, language, and
text processing, and will serve as unifying themes for the workshop.

Among questions to be discussed, we expect:

* Discriminative vs. generative models and algorithms
* Max margin, perceptron, and other criterion
* Incorporating prior knowledge
* Using data from multiple domains
* Adaptation of structured classifiers to new conditions
* Using unlabeled data
* Combining text and speech
* Integrated inference for complex language processing tasks

Program:
--------

This one-day workshop will have survey/tutorial talks in the morning
followed by shorter contributed talks, posters, and discussion
sessions later in the day. The survey talks will present central
themes and questions that will guide the discussion during the
workshop (see below). We are well aware of the tendency to turn
workshops into mini-conferences, so we will make sure by keeping a
tight control on the schedule that there will be sufficient time for
discussion during and after talks. One of the ways we intend to use in
order to accomplish this goal is to assign each of the presenters in
the workshop to serve as discussant for someone else's
presentation. Discussion will be moderated by the organizers.

The survey/tutorial talks are intended to provide a thorough
background and overview of the field from a number of different
perspectives (machine learning, statistics, mathematics, and
applications such as speech, text, and language). In order to better
customize the workshop to the interested audience, the survey/tutorial
talks will be tuned to a set of issues and questions that are raised
on a NIPS workshop discussion web page. The goal is for interested
participants to post any nagging questions or general ideas that they
have to this discussion board. These questions will then become a
basis for the central theme of the workshop. Of course, for this to be
a success it is necessary for people to pose questions to the
discussion board. Therefore, it will be possible for people to post
questions either with their identity associated, or anonymously. See
below for further details.

Potential participants are encouraged to submit (extended) abstracts of
two to four (2-4) pages in length outlining their research as it relates
to the above theme. Papers may show novel ideas or applications related to
structured classification. Encouraged topics include novel theoretical
results, practical application results, novel insight regarding the above,
and/or tips and tricks that work well empirically on a broad range of
data.  Papers should be formatted using the standard NIPS formatting
guidelines.

Schedule and Dates:
--------------------

        - Nov 1st, 2005: Paper submission deadline.
          Email all submissions to:  <[log in to unmask]>
           with subject starting with 'STRUCTLEARN'
           must be a .pdf file
        - Nov 8th, 2005: Acceptance (talks and poster) decisions announced.
        - Dec 9th, 2005: NIPS Workshop date.

Relevant Web pages:

   - NIPS workshop web page:

        http://www.nips.cc/Conferences/2005/Workshops/

   - Discussion Board for Advances in Structured Learning for Text and Speech
Processing

        http://fling-l.seas.upenn.edu/~cse1xx/structlearn/index.php

     Please visit this web page and use it to post questions, problems,
     or ideas about open problems in the structured prediction area that
     you would like to see discussed both during the survey/tutorial
     talks and throughout the rest of the workshop.

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