** The Paris Machine Leanring meetup is on Twitter @ParisMLGroup **
Thank you to Morning coworking for hosting us.
As usual, first come, first served, the room capacity is 120 seats so there is ample space.
Schedule: 6:45PM : doors open / 7PM : talks / 9PM : networking / 10PM : end
Here is the page on the meetup.com platform to register. The streaming will be here:
Antoine Thorin, BRED-Banque Populaire, From reactivity to proactivity in ATM maintenance
Gael Varoquaux, INRIA, Learning with missing valuesHow BRED-Banque Populaire, understand the functioning of ATM, by collecting data from different sources. Visualizes and analyzes data in order to improve the reliability and the availability of ATM.
In many application settings, the data have missing features which make data analysis challenging. An abundant literature addresses missing data in an inferential framework: estimating parameters and their variance from incomplete tables. Here, we consider supervised-learning settings: predicting a target when missing values appear in both training and testing data.https://hal.archives-ouvertes.fr/hal-02024202v2
Gregoire Martinon, Quantmetry, Real-time detection of attacks on ATMs
The general philosophy is to convert video into time series. The standard anomaly detection artillery can then be deployed over the generated time series. To make such a conversion, a combination of tracking detector is used: a deep learning detector allows to locate with great precision an area of interest (face, hand, skeleton), while a tracking device (MOSSE) is in charge of tracking the target from one frame to another. The advantage of the tracker is that it is extremely fast and compensates for the high calculation time of the detector.
Fabien Vauchelles, Zelros
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