JiscMail Logo
Email discussion lists for the UK Education and Research communities

Help for SUPPORT-VECTOR-MACHINES Archives


SUPPORT-VECTOR-MACHINES Archives

SUPPORT-VECTOR-MACHINES Archives


SUPPORT-VECTOR-MACHINES@JISCMAIL.AC.UK


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

SUPPORT-VECTOR-MACHINES Home

SUPPORT-VECTOR-MACHINES Home

SUPPORT-VECTOR-MACHINES  June 2018

SUPPORT-VECTOR-MACHINES June 2018

Options

Subscribe or Unsubscribe

Subscribe or Unsubscribe

Log In

Log In

Get Password

Get Password

Subject:

CFP: 3rd ECML/PKDD 2018 Workshop on IoT Large Scale Machine Learning from Data Streams

From:

Carlos Ferreira <[log in to unmask]>

Reply-To:

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

Date:

Sat, 16 Jun 2018 21:15:45 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (66 lines)

Call for Papers on IoT Large Scale Machine Learning from Data Streams
https://abifet.wixsite.com/iotstreaming2018

3rd ECML/PKDD 2018 Workshop on IoT Large Scale Machine Learning from Data Streams

The volume of data is rapidly increasing due to the development of the technology of information and communication. This data comes mostly in the form of streams. Learning from this ever-growing amount of data requires flexible learning models that self-adapt over time. In addition, these models must take into account many constraints: (pseudo) real-time processing, high-velocity, and dynamic multi-form change such as concept drift and novelty. This workshop welcomes novel research about learning from data streams in evolving environments. It will provide the researchers and participants with a forum for exchanging ideas, presenting recent advances and discussing challenges related to data streams processing. It solicits original work, already completed or in progress. Position papers are also considered. This workshop is combined with a tutorial treating the same topic and will be presented in the same day.

Motivation and focus

The volume of data is rapidly increasing due to the development of the technology of information and communication. This data comes mostly in the form of streams. Learning from this ever-growing amount of data requires flexible learning models that self-adapt over time. In addition, these models must take into account many constraints: (pseudo) real-time processing, high-velocity, and dynamic multi-form change such as concept drift and novelty. Consequently, learning from streams of evolving and unbounded data requires developing new algorithms and methods able to learn under the following constraints: -) random access to observations is not feasible or it has high costs, -) memory is small with respect to the size of data, -) data distribution or phenomena generating the data may evolve over time, which is known as concept drift and -) the number of classes may evolve overtime. Therefore, efficient data streams processing requires particular drivers and learning techniques:

     Incremental learning in order to integrate the information carried by each new arriving data;
     Decremental learning in order to forget or unlearn the data samples which are no more useful;
     Novelty detection in order to learn new concepts.

It is worthwhile to emphasize that streams are often generated by distributed sources, especially with the advent of Internet of Things and therefore processing them centrally may not be efficient especially if the infrastructure is large and complex. Scalable and decentralized learning algorithms are potentially more suitable and efficient.

Aim and scope

This workshop welcomes novel research about learning from data streams in evolving environments. It will provide the researchers and participants with a forum for exchanging ideas, presenting recent advances and discussing challenges related to data streams processing. It solicits original work, already completed or in progress. Position papers are also considered. The scope of the workshop covers the following, but not limited to:

      Online and incremental learning
      Online classification, clustering and regression
      Online dimension reduction
      Data drift and shift handling
      Online active and semi-supervised learning
      Online transfer learning
      Adaptive data pre-processing and knowledge discovery
      Applications in
          Monitoring
          Quality control
          Fault detection, isolation and prognosis,
          Internet analytics
          Decision Support Systems,
          etc.

Submission and Review process

Regular and short papers presenting work completed or in progress are invited. Regular papers should not exceed 12 pages, while short papers are maximum 6 pages. Papers must be written in English and are to be submitted in PDF format online via the Easychair submission interface:https://easychair.org/conferences/?conf=iotstreaming2018

Each submission will be evaluated on the basis of relevance, significance of contribution, quality of presentation and technical quality by at least two members of the program committee. All accepted papers will be included in the workshop proceedings and will be publically available on the conference web site. At least one author of each accepted paper is required to attend the workshop to present.

Important dates

Paper submission deadline: Monday, July 16th, 2018
Paper acceptance notification: Friday, July 27th, 2018
Paper camera-ready submission: Monday, August 6th, 2018

Best regards,




Carlos Ferreira


ISEP | Instituto Superior de Engenharia do Porto
Rua Dr. António Bernardino de Almeida, 431
4249-015 Porto - PORTUGAL
tel. +351 228 340 500 | fax +351 228 321 159
[log in to unmask] | www.isep.ipp.pt

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

To unsubscribe from the SUPPORT-VECTOR-MACHINES list, click the following link:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=SUPPORT-VECTOR-MACHINES&A=1

Top of Message | Previous Page | Permalink

JiscMail Tools


RSS Feeds and Sharing


Advanced Options


Archives

September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013
January 2013
December 2012
November 2012
October 2012
September 2012
August 2012
July 2012
June 2012
May 2012
April 2012
March 2012
February 2012
January 2012
December 2011
November 2011
October 2011
September 2011
August 2011
July 2011
June 2011
May 2011
April 2011
March 2011
February 2011
January 2011
December 2010
November 2010
October 2010
September 2010
August 2010
July 2010
June 2010
May 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
September 2009
August 2009
July 2009
June 2009
May 2009
April 2009
March 2009
February 2009
January 2009
December 2008
November 2008
October 2008
September 2008
August 2008
July 2008
June 2008
May 2008
April 2008
March 2008
February 2008
January 2008
December 2007
November 2007
October 2007
September 2007
August 2007
July 2007
June 2007
May 2007
April 2007
March 2007
February 2007
January 2007
2006
2005
2004
2003
2002
2001
2000


JiscMail is a Jisc service.

View our service policies at https://www.jiscmail.ac.uk/policyandsecurity/ and Jisc's privacy policy at https://www.jisc.ac.uk/website/privacy-notice

Secured by F-Secure Anti-Virus CataList Email List Search Powered by the LISTSERV Email List Manager