Special session on Optimisation and Machine Learning in Data
Large amounts of data are transforming science and engineering, including healthcare, finance, and businesses, and 'big data' is becoming a slogan. Optimisation and machine learning are both high impact areas for today's emerging data science. The aim of this Special Session is to explore new synergies between optimisation and machine learning, and to foster multi-disciplinary discussions in the context of large scale data mining problems.
Research contributions of no more than 8 pages in IEEE format are invited for oral and poster presentation at the Special Session. Innovative ideas and work in progress are especially encouraged.
Topics of interest include, but are not limited to the following:
Hypotheses in data science that call for optimisation or/and machine learning
- New data representations (e.g. compressive and sparse representations)
combinations of machine learning and optimisation able to tackle large scale
- Developments of new models, methodologies and algorithms to advance optimisation and data mining
Practical systems and software to address various optimisation problems that
arise in machine learning and data mining
All submissions will be peer reviewed and accepted papers will be published in the conference proceedings and will be indexed in IEEE Xplore. Further submission details will be posted on the main UKCI2013 web site.
Paper submission deadline:
Special Session Chair
A.Kaban [at] cs.bham.ac.uk