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All streams at EURO 2021 were hybrid. Sessions: TD-55 Data Science and Optimization Patrick De Causmaecker, Ender Özcan, Daniel Karapetyan TE-55 Optimization Models for Machine Learning Dimitri Papadimitriou TF-55 Better Decisions with Data II Yingqian Zhang WA-55 Data-driven decisions in OR Hatice Calik, Victor Bucarey WB-55 Integrating machine learning in optimization methods I Kevin Tierney […]
The workshop co-chairs are: Patrick De Causmaecker (KU Leuven, BE) Tias Guns (Vrije Universiteit Brussel, BE Michele Lombardi (University of Bologna, IT) Yingqian Zhang (TU Eindhoven, NL) Data science and optimization are closely related. On the one hand, many problems in data science can be solved using optimizers, on the other hand optimization problems stated […]
Building on the streams at IFORS 2017 in Quebec, EURO 2018 in Valencia, Euro 2019 in Dublin, it is our pleasure to announce the stream at IFORS 2020 in Seoul. See the sessions here and feel free to use the codes when submitting your abstract
Location: room 00.21A, IICK building, KU Leuven, campus Kortrijk, Etienne Sabbelaan 53, 8500 Kortrijk Date: 10th and 11th, March, 2020 We are pleased to announce the symposium organized at KU Leuven, campus Kortrijk on the 10th and 11th of March. We will have six speakers along with a poster session with the participants from different […]
Data science and optimisation are closely related. On the one hand, many problems in data science can be solved using optimisers, on the other hand optimisation problems stated through classical models such as those from Mathematical Programming cannot be considered independent of historical data. Examples are ample. Machine learning often relies on optimisation techniques such […]
Building on the succes of the 2018 stream with 11 presentations, 44 contributions and interesting discussions, we set up a similar stream in this year’s edition. Again, the two directions implied by the ‘meet’ keyword will be present. Concretely the following sessions have been initialised: The Role of Mathematical Optimization in Data Science, Vanesa Guerrero […]
DSO Workshop at FEDERATED ARTIFICIAL INTELLIGENCE MEETING 2018 (DSO@FAIM) Keynote speakers Schedule Data science and optimisation are closely related. On the one hand, many problems in data science (data mining, machine learning, statistical methods, but also problems set in constraint programming) can be solved using optimisers, on the other hand optimisation problems stated […]
Stream at EURO 2018 in Valencia Organisers Patrick De Causmaecker (Patrick.DeCausmaecker@kuleuven.be) Ender Özcan (ender.ozcan@nottingham.ac.uk) Andrew J. Parkes (ajp@cs.nott.ac.uk) Dolores Romero Morales (drm.eco@cbs.dk) List of abstracts: EURO2018 Sessions The Role of Mathematical Optimization in Data Science I, Chair: Vanesa Guerrero Integrating Machine Learning in Optimization Methods, Chair: Kevin Tierney Optimization of Machine Learning Models, Chair: Dimitri Papadimitriou […]
Data Science meets Optimisation Streams 2017 Call for Abstracts Stream on Data Science meets Optimisation Quebec city, Quebec, Canada (July 17-21, 2017) Scope: The interaction of data science (DS) and optimisation (O) is the central theme of the working group (DSO). DSO originates from the observation that, on the one hand, real time optimisation algorithms are tightly linked to […]
DSO workshop colocated with CEC 2017 and CPAIOR 2017 INVITED SPEAKERS: On the role of (machine) learning in (mathematical) optimization Andrea Lodi In this talk, I try to explain my point of view as a Mathematical Optimizer -- especially concerned with discrete (integer) decisions -- on Big Data. I advocate a tight integration of Machine Learning and Mathematical […]