New England Machine Learning Day

 

We are thrilled to announce the first New England Machine Learning Day (NEML), which will be held May 16th, 2012 at Microsoft Research New England. The event will bring together local researchers in machine learning and those who use machine learning in applications. There will be a lively poster session during lunch.

Invited speakers:

* Edo Airoldi (Harvard)
* Regina Barzilay (MIT)
* Pedro Felzenszwalb (Brown)
* Tommi Jaakkola (MIT)
* Ce Liu (MSR)
* Andrew McCallum (UMass Amherst)
* Ohad Shamir (MSR)
* Leslie Valiant (Harvard)

To help us plan for food and seating, if you expect to attend, please RSVP by sending an email to mlday@microsoft.com with your name and affiliation. If registration exceeds capacity, those who have registered earliest will receive priority.

To submit a poster, please email a brief abstract describing the project to nemlposter@hotmail.com by May 5th, 2012. Please also encourage relevant students to attend and submit posters.

For more information/updates, see the website at: http://research.microsoft.com/neml2012

Please help us publicize the event! If you know of appropriate mailing lists, could you please forward this info. Hope to see you there.

Best,
The organizers
Sham Kakade (Microsoft Research, Chair) Ryan Adams (Harvard) Adam Tauman Kalai (Microsoft Research) Cynthia Rudin (MIT) Joshua Tenenbaum (MIT)

Call for Papers: IEEE PAMI Special Issue

 

Call for Papers
IEEE Transaction on Pattern Analysis and Machine Intelligence Special Issue on Bayesian Nonparametrics

Bayesian nonparametric models are probabilistic models defined over infinite dimensional parameter spaces. Examples include Gaussian processes, used in regression and classification, where the parameter space consists of the set of smooth functions, and Dirichlet process mixture models for density estimation problems, where the parameter space is dense in the space of densities. Bayesian nonparametrics present a flexible framework for modeling complex data and a viable alternative to model selection, and have gained increasing attention in machine learning, statistics, and related fields in recent years.

We invite paper submissions for a special issue on Bayesian nonparametrics to be published in IEEE Transactions in Pattern Analysis and Machine Intelligence. Original research papers as well as overview and survey papers are welcome, on topics including, but not limited to:

  • Statistical and learning theory for Bayesian nonparametric methods
  • Novel Bayesian nonparametric models and stochastic processes
  • Novel methodologies for learning and inference, including Monte Carlo, variational, message-passing, online, and large scale algorithms
  • Applications, to signal processing, image processing, speech, language processing and others

Priority will be given to papers with high novelty and originality for research papers, and to papers with high potential impact for survey/overview papers.

Paper submission and review:
We invite interested authors to submit 2-page white papers outlining their submission by June 30, 2012, by email to
npbayes2012pami@gmail.com

Feedback on the white paper will be provided, and suitable submissions invited to submit full papers online, by August 31, 2012, through the TPAMI site at,
https://mc.manuscriptcentral.com/tpami-cs

selecting the choice that indicates this special issue. Peer reviewing will follow the standard IEEE review process. Full length manuscripts are expected at this second stage, following the TPAMI guidelines in http://www.computer.org/portal/web/peerreviewjournals/author

Time line:
Submission of 2-page white papers: June 30, 2012.
Feedback and invitations to submit full papers: July 15, 2012.
Submission of full papers: August 31, 2012.
First reviews: November 15, 2012.
Revisions due: January 15, 2013.
Decisions announced: February 28, 2013.
Final manuscripts due: March 31, 2013.

Guest editors:

IMS/ASA Spring Research Conference

 

This year's IMS/ASA Spring Research Conference ("Enabling the Interface Between Statistics and Engineering") will be occurring here at Harvard, hosted jointly by SEAS and the Department of Statistics.

NIPS Workshop on Bayesian Nonparametrics

 

Ryan Adams and Emily B. Fox (University of Pennsylvania) will be organizing a workshop entitled "Bayesian Nonparametric Methods: Hope or Hype?" with speakers such as Zoubin Ghahramani, Alex Smola, and Chris Holmes. The workshop will be associated with the Neural Information Processing Systems conference in Granada, Spain. The workshop is currently accepting contributions. More information can be found at the webpage.