LIRIS news
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A new fuzzy switching filter for time series denoising
How to denoise non-stationary data with progressive transitions between 2 states, such as temperatures measured during day/night rotations? To solve this type of problem, we propose a new Gaussian linear fuzzy filtering algorithm, which is optimal and fast.
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Links between odorant structure and olfactory perception revealed thanks to artificial intelligence
Can we verbally describe an odorant compound only by looking at its chemical structure? This exercise remains a challenge for scientists and a fantasy for the aroma and fragrance industry. This work, published in Plos Computational Biology, has combined innovative pattern mining approaches with chemical property calculations to establish such rules. A fruitful interdisciplinary collaboration for a first step on the way to the rational design of perfume compounds.
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The DM2L research group from LIRIS at SIGKDD 2019.
The DM2L research group, in collaboration with the University of Ghent (Belgium), will present at SIGKDD’19 a novel method to analyse data with hierarchies.
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Inauguration of the Labcom Behavior.ai (Joint Laboratory between LIRIS and Hoomano)
The inauguration of labcom Behavior.ai, a joint laboratory between LIRIS and Hoomano, funded by the ANR was successfully held on April 10th, 2019.
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Équipe TWEAK - Traces d'agents autonomes
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Équipe TWEAK - Ambre Web : un environnement pour l'apprentissage de méthodes de résolution de problèmes en primaire
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Équipe SAARA - Suivi de la respiration par acquisition multi-modale en temps réel
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Équipe SICAL - Pupitres interactifs
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équipe TWEAK - Sympozer, une application Web mobile pour l’agrégation de données de conférences provenant de différentes sources
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Équipe M2DisCo - Courbure moyenne sur un objet discret (bruité ou non) par une approche Integral Invariant
Diary
From 15/10/2019 at 09:00 to 18/10/2019 at 16:30. Place: Campus de la Doua - Rotonde
French conference on databases and data management
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Recent publications
- Johannes Jurgovsky, Michael Granitzer, Konstantin Ziegler, Sylvie Calabretto, Pierre-Edouard Portier, Liyun He-Guelton & Olivier Caelen (2018). « Sequence Classification for Credit-Card Fraud Detection ». Expert Systems with Applications, pp. 234-245. doi : 10.1016/j.eswa.2018.01.037. HAL : hal-01699528.
- Yannick Faula, Stéphane Bres & Véronique Eglin (2018). « FLASH: a new key structure extraction used for line or crack detection and image matching ». International Conference on Computer Vision Theory and Applications (Visapp 2018), 29 janvier 2018, Funchal, Madeira (Portugal). HAL : hal-01636680.
- Hélène Perrier, David Coeurjolly, Feng Xie, Matt Pharr, Pat Hanrahan & Victor Ostromoukhov (2018). « Sequences with Low-Discrepancy Blue-Noise 2-D Projections ». Computer Graphics Forum, vol. 37, n°2, pp. 339-353. HAL : hal-01717945.
. - Guillaume Cordonnier, Pierre Ecormier, Eric Galin, James Gain, Bedrich Benes & Marie-Paule Cani (2018). « Interactive Generation of Time-evolving, Snow-Covered Landscapes with Avalanches ». Computer Graphics Forum, vol. 37, n°2, pp. 497-509. doi : 10.1111/cgf.13379. HAL : hal-01736971. .
- Morgan Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré & Jean-Luc Starck (2018). « Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning ». SIAM Journal on Imaging Sciences, vol. 11, n°1, pp. 643-678. doi : 10.1137/17M1140431. ArXiv : 1708.01955. HAL : hal-01717943. .
- Bastien Moysset, Christopher Kermorvant & Christian Wolf (2018). « Learning to detect, localize and recognize many text objects in document images from few examples ». International Journal on Document Analysis and Recognition. doi : 10.1007/s10032-018-0305-2. HAL : hal-01800636.