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Schedule
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Thursday 11:00 - 12:20 Routing Problems Room 138 - Chair: Pieter Vansteenwegen
Thursday 11:00 - 12:20 Emergency operations scheduling Room 130 - Chair: El-Houssaine Aghezzaf
Thursday 11:00 - 12:20 Algorithm design Room 126 - Chair: Gerrit Janssens
Thursday 11:00 - 12:20 Multiple Objectives Room 120 - Chair: Filip Van Utterbeeck
Thursday 13:30 - 14:50 Integrated logistics Room 138 - Chair: Kris Braekers
Thursday 13:30 - 14:50 Person transportation Room 130 - Chair: Célia Paquay
Thursday 13:30 - 14:50 Continuous models Room 126 - Chair: Nicolas Gillis
Thursday 13:30 - 14:50 Integer programming Room 120 - Chair: Bernard Fortz
Thursday 15:20 - 16:20 Material handling and warehousing 1 Room 138 - Chair: Greet Vanden Berghe
Thursday 15:20 - 16:20 Operations management Room 130 - Chair: Roel Leus
Thursday 15:20 - 16:20 Matrix factorization Room 126 - Chair: Pierre Kunsch
Thursday 16:30 - 17:10 Material handling and warehousing 2 Room 138 - Chair: Katrien Ramaekers
Thursday 16:30 - 17:10 Routing and local search Room 130 - Chair: An Caris
Thursday 16:30 - 17:10 Traffic management Room 126 - Chair: Joris Walraevens
Thursday 16:30 - 17:10 Pharmaceutical supply chains Room 120 - Chair: Bart Smeulders
Friday 10:50 - 12:10 Optimization in health care Room 138 - Chair: Jeroen Beliën
Friday 10:50 - 12:10 Network design Room 130 - Chair: Jean-Sébastien Tancrez
Friday 10:50 - 12:10 Local search methodology Room 126 - Chair: Patrick De Causmaecker
Friday 10:50 - 12:10 ORBEL Award Room 120 - Chair: Frits Spieksma
Friday 13:00 - 14:00 Production and inventory management Room 138 - Chair: Tony Wauters
Friday 13:00 - 14:00 Logistics 4.0 Room 130 - Chair: Thierry Pironet
Friday 13:00 - 14:00 Data clustering Room 126 - Chair: Yves De Smet
Friday 13:00 - 14:00 Collective decision making Room 120 - Chair: Bernard De Baets
Friday 14:10 - 15:10 Sport scheduling Room 138 - Chair: Dries Goossens
Friday 14:10 - 15:10 Discrete choice modeling Room 130 - Chair: Virginie Lurkin
Friday 14:10 - 15:10 Data classification Room 126 - Chair: Ashwin Ittoo
- A density-based decision tree for one-class classification
Sarah Itani (University of Mons) Co-authors: Fabian Lecron & Philippe Fortemps Abstract: One-Class Classification (OCC) aims at predicting a single class on the basis of its lonely training representatives, called target instances. This mode of classification is thus opposed to common prediction problems with two or several classes. As data availability is not necessarily ensured for a good number of medical and industrial applications, OCC presents itself as an interesting alternative methodology. Our proposal addresses OCC through a decision tree. The related learning process is driven by density estimation.
- Comparison of active learning classification strategies
Xavier Siebert (Faculté Polytechnique de Mons) Co-authors: Nouara Bellahdid, Moncef Abbas
- Risk bounds on statistical learning
Boris Ndjia Njike (Université de Mons) Co-authors: Xavier Siebert
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ORBEL - Conference chair: Prof. A. Arda -
Platform: Prof. M. Schyns.
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