CITI Talk: “Deep Learning: history, models & challenges, with an application in signal processing and mobile authentification”, Ass. Prof. Christian Wolf (INSA Lyon, CITI-LIRIS), 22/02/2018, TD C

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Deep Learning: history, models & challenges, with an application in signal processing and mobile authentification


Representation Learning (also known with its more popular title « Deep Learning ») consists in automatically learning layered and hierarchical representation with various layers abstraction from large amounts of data. This presentation will review the history of the field, the main actors and the major scientific challenges. We will first present a brief introduction into common deep models like convolutional neural networks and recurrent networks, before going more into detail of some selected applications in signal processing.

In particular, we present a large-scale study, exploring the capability of temporal deep neural networks in interpreting natural human kinematics and introduce the first method for active biometric authentication with mobile inertial sensors. This work has been done in collaboration with Google, where the first-of-its-kind dataset of human movements has been passively collected by 1500 volunteers using their smartphones daily over several months. We propose an optimized shift-invariant dense convolutional mechanism (DCWRNN) and incorporate the discriminatively-trained dynamic features in a probabilistic generative framework taking into account temporal characteristics. Our results demonstrate, that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems.


Christian WOLF is associate professor (Maitre de Conférences, HDR) at INSA de Lyon and LIRIS UMR 5205, a CNRS laboratory, since 2005. He is interested in computer vision and machine learning, deep learning, especially in the visual analysis of complex scenes in motion: gesture and activity recognition and pose estimation. In his work he puts an emphasis on models of complex interactions, on structured models, graphical models and on deep learning. He received his MSc in computer science from Vienna University of Technology (TU Wien) in 2000, and a PhD in computer science from INSA de Lyon, France, in 2003. In 2012 he obtained the habilitation diploma, also from INSA de Lyon. Since September 2017 Christian is on leave at INRIA, at the chroma work group at the CITI laboratory (“délégation INRIA”).