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DTSTART;TZID=Europe/Brussels:20250313T130000
DTEND;TZID=Europe/Brussels:20250313T140000
DTSTAMP:20260415T035014
CREATED:20241016T085444Z
LAST-MODIFIED:20250109T150055Z
UID:2208-1741870800-1741874400@www.naxys.be
SUMMARY:Hélène Verhaeghe (UCLouvain)
DESCRIPTION:Title : The best of both worlds: when constraint programming and machine learning help each other \nAbstract : Constraint programming is well known to be performant at finding the solutions of combinatorial optimization problems and can provide guarantees about these solutions. However\, as problems tend to grow in size and complexity\, the limits of such methods tend to show. Machine learning\, on the other hand\, is very good at extracting statistical patterns and dealing with uncertainty. However\, they are really bad at reasoning\, even on simple tasks. This talk is about how\, by combining the two families of techniques\, they can benefit one another. This talk will start with an introduction to constraint programming for those not knowledgeable about the technique. \nThe seminar will take place in Room S08 at the Faculty of Sciences.
URL:https://www.naxys.be/event/helene-verhaeghe-uclouvain/
CATEGORIES:NAXYS Seminar
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DTSTART;TZID=Europe/Brussels:20250320T130000
DTEND;TZID=Europe/Brussels:20250320T140000
DTSTAMP:20260415T035014
CREATED:20241016T130022Z
LAST-MODIFIED:20250317T084306Z
UID:2213-1742475600-1742479200@www.naxys.be
SUMMARY:Jérémy Rekier (Royal Observatory of Belgium)
DESCRIPTION:Title : The Tidal Flows in Ocean Worlds \nAbstract : \nPlanet Earth is one of a handful of ocean worlds in the solar system. Others include Jupiter’s moons Europa\, Ganymede and Callisto\, as well as Saturn’s moons Titan and Enceladus. Other such worlds might also exist in orbit around Uranus and Neptune. In all of these bodies\, tidal heating plays a crucial role in keeping the water ocean from freezing\, thereby extending the habitable zone beyond its classical circumstellar (aka Goldilocks) limit. Some authors even consider that such worlds orbiting exoplanets might be more habitable than analogues to the Earth. This makes exploration of the ocean worlds that are closer to us crucial in order to understand the conditions for extraterrestrial life\, and this involves paying close attention to the process of tidal heating. \nExploration of the fluid dynamics of icy moons is a complicated matter\, in large part due to the subsurface nature of their oceans. We present some of the methods developed to this end\, inspired by previous work focusing on the study of the Earth’s and planet’s deep interior. We show how tidal flows can be resonantly amplified by inertial modes (restored by the Coriolis force) in liquid oceans\, and how these modes are affected by density stratification. \nThe seminar will take place in Room S08 at the Faculty of Sciences.
URL:https://www.naxys.be/event/jeremy-rekier-royal-observatory-of-belgium/
CATEGORIES:NAXYS Seminar
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DTSTART;TZID=Europe/Brussels:20250327T130000
DTEND;TZID=Europe/Brussels:20250327T140000
DTSTAMP:20260415T035014
CREATED:20250109T133752Z
LAST-MODIFIED:20250305T111016Z
UID:2291-1743080400-1743084000@www.naxys.be
SUMMARY:Hugues Annoye (UCLouvain Saint-Louis)
DESCRIPTION:Title : BEAMM project : How do we deal with data ? Statistical matching and WGAN generation. \nAbstract : \n\n\n\nIn the framework of the BEAMM project (BElgian Arithmetic Micro-simulation Model)\, we propose several methods to address data issues. The core of this project is to develop a tax-benefit microsimulation model for Belgium accessible online\, requiring intensive data handling. Our challenges consist in creating a unified data set containing variables from different surveys and developing a completely synthetic database for the online development of the BEAMM platform. \nIndeed\, in the BEAMM context\, we use a large number of variables available in different databases. We thus need to analyze data from different sources; the obser- vations\, which only share a subset of the variables\, cannot always be paired to detect common individuals. This is the case\, for example\, when the information required to study a certain phenomenon comes from different sample surveys. Statistical matching is a common practice to combine these data sets. In this talk\, we investigate and extend to statistical matching three methods based on Kernel Canonical Correlation Analy- sis (KCCA; [2])\, Super-Organizing Map (Super-OM; [1]) and Autoencoders-Canonical Correlation Analysis (A-CCA; [3]). These methods are designed to deal with various variable types\, sampling weights and incompatibilities among categorical variables. \nIn our context\, data privacy and anonymization are important. Under these cir- cumstances\, the need for synthetic databases that replicate the characteristics of the population while preserving privacy is arising. In this presentation\, we also investigate how we can employ a range of data generation approaches utilizing various advance- ments in the Wasserstein Generative Adversarial Network (WGAN) literature to create survey databases. WGANs were introduced by Arjovsky 2017 [4] in the context of im- age synthesis. Our algorithms have been adjusted to account for sampling weights. Moreover\, survey and adminstrative data have the specificity of mixing continuous and categorical data\, which should be taken into account in the architecture of the WGANs. \n\nReferences : \n\n\n\n[1] Kohonen\, T. (1982)\, Self-organized formation of topologically correct feature map. Biological Cybernetics\, 43 (1)\, 59–69. \n\n\n\n\n\n\n[2] Lai\, P. L. and Fyfe\, C. (2000)\, Kernel and nonlinear canonical correlation analysis. International Journal of Neural Systems\, 10 (05)\, 365–377. \n\n\n\n[3] Rumelhart\, D. E.\, Hinton\, G. E. and Williams\, R. J. (1986)\, Learning Internal Representations by Error Propagation in Parallel Distributed Processing: Explo- rations in the Microstructure of Cognition. Cambridge: MIT Press\, 318–362. \n\n\n\n\n\n\n\n\n\n\n\n[4] Arjovsky\, M.\, Chintala\, S.\, & Bottou\, L. (2017\, July). Wasserstein generative adversarial networks.In International conference on machine learning (pp. 214- 223). PMLR. \n\n\n\nThe seminar will take place in Room S08 at the Faculty of Sciences.
URL:https://www.naxys.be/event/hugues-annoye-uclouvain-saint-louis/
CATEGORIES:NAXYS Seminar
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