ReLSD 2015 - Representation Learning for Semantic Data workshop (ReLSD)

Representation Learning for Semantic Data workshop (ReLSD)
Joint with ICDM-2015
Call for papers
Important Dates
Submission deadline: July 20, 2015
Acceptance notification: September 01, 2015
Final paper submission: September 15, 2015
Workshop date: November 14, 2015
Workshop site: http://pris.net.cn/wp-content/uploads/ReLSD2015/
Objectives
The focus of this workshop will be on representation learning approaches applied to semantic data emerging from real world. New models and learning algorithms based on representation learning that can address all of the challenges in semantic data mining are encouraged. This one-day workshop will include a mixture of invited talks, and contributed presentations, which will cover a broad range of subjects pertinent to the workshop theme. Besides classical paper presentations, the call also includes demonstration for applications on these topics. We believe this workshop will accelerate the process of identifying the power of representation learning operating on semantic data. This is the second edition of this workshop, the first one being held at ECML in 2014.
Topics of Interest
The focus of this workshop will be on representation learning approaches, including deep learning, feature learning, metric learning, algebraic and probabilistic latent models, dictionary learning and other compositional models, to solving problems in semantic data mining. Papers on new models and learning algorithms that combine aspects of the two fields of representation learning and semantic data mining are especially welcome.
A non-exhaustive list of relevant topics:
- unsupervised representation learning and its applications
- supervised representation learning and its applications
- metric learning and kernel learning and its applications
- hierarchical models on data mining
- optimization for representation learning
- other related applications based on representation learning.
We also encourage submissions which relate research results from other areas to the workshop topics.
Workshop Organizers
Patrick Gallinari: Université Pierre et Marie Curie, France ( Patrick.Gallinari-AT-lip6.fr )
Sang-Wook Kim:Hanyang University, Korea ( wook-AT-hanyang.ac.kr )
Jun Guo：Beijing University of Posts and Telecommunications, China
( guojun-AT-bupt.edu.cn )
Sheng Gao: Beijing University of Posts and Telecommunications, China
( gaosheng-AT-bupt.edu.cn )
Submission of Papers
We invite two types of submissions for this workshop:
n Paper submission
We welcome submission of unpublished research results. Paper length should be limited to a maximum of 8 pages in the IEEE 2-column format. Papers should be typeset using the IEEE Computer Society proceedings manuscript style, though the submissions do not need to be anonymous. All submissions will be anonymously peer reviewed and will be evaluated on the basis of their technical quality. Submissions must be made through the official system:
https://wi-lab.com/cyberchair/2015/icdm15/scripts/....
By the unique ICDM tradition, all accepted workshop papers will be published in a formal proceedings published by the IEEE Computer Society Press. We will also motivate the contributors by selecting some accepted papers to publish in a special issue “Deep Machine Learning for Semantic Data” in a SCI Journal, which will come out in early 2016.