Speaker: Prof. Yuhui Shi
Southern University of Science and Technology (SUSTech), Shenzhen, China Title: Introduction to Brain Storm Optimization Algorithms
Date: Tuesday 3 October 2017 Time: 11:30 – 12:30 Venue: 09.03.12 (Building 9, Level 3, Room 12), RMIT City Campus
Abstract: Swarm intelligence (SI) algorithms, a collection of population-based optimization algorithms, have been being designed and researched to solve problems which are very difficult, if not impossible, for traditional optimization approaches such as hill-climbing approaches to solve. Most existing SI algorithms are nature-inspired and/or bio-inspired, especially are inspired by objects with low level intelligence. Inspired by the brainstorming process, one of the human being problem solving skills, in the year 2011, the brain storm optimization (BSO) algorithm, a new population-based swarm intelligence algorithm, was developed. In this talk, the brainstorming process will be introduced first, followed by the development of the brain storm optimization algorithm; then new advances on BSO will be presented; finally, the BSOs will be looked at from the developmental learning perspective.
Bio: Dr. Yuhui Shi is a Chair Professor in the Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China. Before joining SUSTech, he was with the Department of Electrical and Electronic Engineering at the Xi’an Jiaotong-Liverpool University (XJTLU), Suzhou, China, from January 2008 to August 2017, and was with the Electronic Data Systems Corporation (EDS), Indiana, USA, from October 1998 to December 2007. He is an IEEE Fellow, the Editor-in-Chief of the International Journal of Swarm Intelligence Research, and an Associate Editor of the IEEE Transactions on Evolutionary Computation. Dr. Shi co-authored a book on Swarm Intelligence together with Dr. James Kennedy and Dr. Russell C. Eberhart, and another book on Computational Intelligence: Concept to Implementation together with Dr. Russell C. Eberhart.
Speaker: Prof. Tias Guns
Vrije Universiteit Brussel Title: Pattern mining using constraint programming Date and Time: Fri 8 September 2017 11:30am–12:30pm Location: 80.10.017 (RMIT City Campus) Abstract: In todays data-rich world, pattern mining techniques allow us to extract knowledge from data. However, such knowledge can take many forms and often depends on the application at hand. This calls for generic techniques that can be used in a wide range of settings. Declarative constraint-based mining offers an answer to this question.
By building on constraint programming solvers, a generic method that fits many pattern mining settings is obtained. However, there is a trade-off between generality and efficiency. This talk will discuss multiple efforts to reduce the trade-off, both at the modeling level and at the solving level. Bio: Tias Guns is Assistant Professor at the Vrije Universiteit Brussel (VUB), in the Business, Technology and Operations lab of the faculty of Economic and Social Sciences & Solvay Business School. His research lies on the border between data mining and constraint programming, and his main interest is in integrating domain expertise and user constraints into data analytics tasks. As part of his PhD, he has developed the CP4IM framework which showed for the first time the potential of using constraint programming for pattern mining. His PhD was awarded with both the constraint programming dissertation award and the ECCAI artificial intelligence dissertation award. He is an active member of the community and has organized a number of workshops and a special issue on the topic of combining constraint programming with machine learning and data mining.