The 11th ICDM Workshop on High Dimensional Data Mining (HDM 2024)

In conjunction with the IEEE International Conference on Data Mining : 9-12 December 2024, Abu Dhabi, UAE

Description of Workshop

Unprecedented technological advances lead to increasingly high dimensional data sets in all areas of science, engineering and businesses. These include genomics and proteomics, biomedical imaging, signal processing, astrophysics, finance, web and market basket analysis, among many others. Propelled by the new awareness in the importance of data, practitioners from all areas maintain large repositories of high-dimensional data, albeit only some of them are tagged/labelled, most are unlabelled raw data waiting to be taken advantage of. The number of features in such data is often of the order of thousands or millions, that is much larger than the available (labelled or unlabelled) sample size.

Moreover, high dimensional data with limited sample sizes come with a number of challenges:

High dimensional geometry defeats our intuition rooted in low dimensional experiences, which makes data presentation and visualisation particularly challenging.
Phenomena that occur in high dimensional probability spaces, such as the concentration of measure, are counter-intuitive for the data mining practitioner. For instance, distance concentration is the phenomenon that the contrast between pairwise distances may vanish as the dimensionality increases
Bogus correlations and misleading estimates may result when trying to fit complex models for which the effective dimensionality is too large compared to the number of data points available.
The accumulation of noise may confound our ability to find low dimensional intrinsic structure hidden in the high dimensional data.
The computation cost of processing high dimensional data or carrying out optimisation over high dimensional parameter domains is often prohibiting.

This workshop aims to bring together researchers from databases, data science, machine learning, statistics to cross-pollinate ideas, facilitate collaboration, and expand the breadth and reach of methods and technology to address the curses, exploit the blessings of high dimensionality in data mining, and forge new directions in data mining research.

Topics

This year we would like to particularly encourage work that counters the issues of low sample size and takes advantage of unlabelled or auxiliary data for high dimensional data mining. Topics of interest include (but are not limited to) the following:

Learning and mining with weak supervision, and exploiting unlabelled data in high dimensional settings.
Managing the tradeoff between computation cost and statistical efficiency.
Models of low intrinsic structure, such as sparse representation, manifold models, latent structure models, overparametrised models, compressible models.
Effect and mitigation of noise and the curse of dimensionality on data mining methods.
Theoretical underpinning of data mining where the data dimension can be larger than the sample size.
New data mining techniques that exploit properties of high dimensional data spaces.
Adaptive and non-adaptive dimensionality reduction for high dimensional data sets.
Random projections, and random matrix theory applied to high dimensional data mining.
Functional data mining.
Data mining applications to real problems in science, engineering, businesses, and the humanities, where the data is high dimensional.

Submission Instructions

High quality original submissions are solicited for oral and poster presentation at the workshop. The page limit of workshop papers is 8 pages in the standard IEEE 2-column format (link to the template), including the bibliography and any possible appendices. Reviewing is triple-blind! Therefore, please do not include author identifying information. All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2024 submission guidelines, which are the same as for the main conference (except the page limit). All accepted workshop papers will be published in the IEEE Computer Society Digital Library (CSDL) and IEEE Xplore, and indexed by EI.

Important Dates

Submission deadline: September 10, 2024 via Submission site
Notification of workshop papers acceptance: October 7, 2024
Camera-ready deadline: October 11, 2024
Workshops date: December 9, 2024

Registration & Expenses

Every workshop paper must have at least one full paid conference registration in order to be published. Check the main conference pages for details.

Program Committee

Andrew Starkey

Ata Kaban

Efstratios Palias

Frank-Michael Schleif

Jakramate Bootkrajang

Papangkorn Inkaew

Peter Andras

Momodou Sanyang

Workshop Organisation and Contacts

Ata Kaban: School of Computer Science, University of Birmingham, UK
Jakramate Bootkrajang: Department of Computer Science, Chiang Mai University, Thailand