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X-WR-CALNAME:Computational Optimisation Group
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X-WR-CALDESC:Events for Computational Optimisation Group
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DTSTART;TZID=UTC:20151014T153000
DTEND;TZID=UTC:20151014T153000
DTSTAMP:20260501T064658
CREATED:20170124T102136Z
LAST-MODIFIED:20170124T102136Z
UID:550-1444836600-1444836600@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Generating structured music with local search and machine learning
DESCRIPTION:Title: Generating structured music with local search and machine learningSpeaker: Dr. Dorien HerremansAffiliation: School of Electronic Engineering and Computer Science – Queen Mary UniversityLocation: LT 144 Huxley BuildingTime: 3:30pm \nAbstract. Many state of the art music generation/improvisation systems generate music that sounds good on a note-to-note level. However\, these compositions often lack long term structure or coherence. By looking at generating music as an optimization problem\, this research overcomes this problem and generates music that has a larger structure. A powerful variable neighbourhood search algorithm (VNS) was developed\, which is able to generate a range of musical styles based on it’s objective function\, whilst constraining the music to a structural template. In the first stage of the project\, an objective function based on rules from music theory was used to generate counterpoint. In this research\, a machine learning approach is combined with the VNS in order to generate structured music for the bagana\, an Ethiopian lyre. Different ways are explored in which a Markov model can be used to construct quality metrics that represent how well a fragment fits the chosen style (e.g. music for bagana). Current research that aims to extend the objective function with models such as recursive neural networks is also briefly discussed. The approach followed in this research allows us to combine the power of machine learning methods with optimization algorithms. \nAbout the speaker. Dorien Herremans is currently a Marie Skodowska-Curie Postdoctoral Fellow at C4DM\, Queen Mary University of London. She got her PhD in Operations Research on the topic of Computer Generation and Classification of Music through Operations Research Methods (Compose: Compute – Generating and Classifying Music through Operations Research Methods). She graduated as a commercial engineer in management information systems at the University of Antwerp in 2005. After that\, she worked as a Drupal consultant and was an IT lecturer at the Les Roches University in Bluche\, Switzerland. She also worked as a mandaatassistent at the University of Antwerp\, in the domain of operations management\, supply chain management and operations research (OR). Her current research focuses on applications of OR in the field of music.
URL:http://optimisation.doc.ic.ac.uk/event/seminar-generating-structured-music-with-local-search-and-machine-learning/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20151016T150000
DTEND;TZID=UTC:20151016T150000
DTSTAMP:20260501T064658
CREATED:20170124T102136Z
LAST-MODIFIED:20170124T102136Z
UID:549-1445007600-1445007600@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Families of Convex and Non-Convex Composite Optimization Problems for Signal Processing and Computer Vision
DESCRIPTION:Title: Families of Convex and Non-Convex Composite Optimization Problems for Signal Processing and Computer VisionSpeaker: Dr. Stefanos ZafeiriouAffiliation: Department of Computing – Imperial College LondonLocation: Room 217 – 218 Huxley BuildingTime: 3:00pm \nAbstract.  \nAbout the speaker. Stefanos Zafeiriou is a Senior Lecturer (equivalent to Associate Professor) in Pattern Recognition/Statistical Machine Learning for Computer Vision in the Department of Computing\, Imperial College London. He has been awarded one of the prestigious Junior Research Fellowships (JRF) from Imperial College London in 2011 to start his own independent research group. He is/has participated in more than 10 EU\, British and Greek research projects. Dr. Zafeiriou currently serves as an Associate Editor in IEEE Transactions on Cybernetics and  Image and Vision Computing journal. He has been guest editor in more than four special issues and co-organized more than five workshops/ special sessions in top venues such as CVPR/FG/ICCV/ECCV.  He has co-authored more than 40 journal papers mainly on novel statistical machine learning methodologies applied to computer vision problems such as 2D/3D face and facial expression recognition\, deformable object tracking\, human behaviour analysis etc published in the most prestigious journals in his field of research (such as IEEE T-PAMI\, IJCV\, IEEE T-IP\, IEEE T-NNLS\, IEEE T-VCG\, IEEE T-IFS etc). His students are frequent recipients of very prestigious and highly competitive fellowships such as Google Fellowship\, Intel Fellowship and the Qualcomm fellowship. He has more than 2000 citations to his work\, h-index 24.
URL:http://optimisation.doc.ic.ac.uk/event/seminar-families-of-convex-and-non-convex-composite-optimization-problems-for-signal-processing-and-computer-vision/
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