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Laboratoire d'InfoRmatique en Image et Systèmes d'information

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Laboratoire d'InfoRmatique en Image et Systèmes d'information
UMR 5205 CNRS / INSA de Lyon / Université Claude Bernard Lyon 1 / Université Lumière Lyon 2 / École Centrale de Lyon
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Johannes Jurgovsky

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PhD student

Team Distributed Systems, Information Retrieval and Mobility
 
Institution Institut National des Sciences Appliquées de Lyon
Location Blaise Pascal (INSA)
 
E-mail johannes.jurgovsky at liris.cnrs.fr
Contact details Publications Thesis
 
Subject Efficient Representations with Deep Learning
Abstract In my doctoral thesis, I’m exploring different methods for an automatic extraction and representation of valuable information from data. In particular, I’m working with discrete time series data in which the events of interest occur only very rarely in the form of anomalies. Such anomalies are not necessarily atomic but distributed across several measurements in the temporal stream. A key step here is to develop models for both the evolution of legitimate events and the anomalies by using supervised and unsupervised learning methods. From these models I aim to extract concise representations that summarize the characteristics of temporal patterns, such that, an inexpensive comparison of these representations reveals the commonalities and differences of the original temporal patterns. I also investigate means to exploit and integrate knowledge from Linked Open Data for the purpose of enriching the data stream with additional information.
Advisor Sylvie Calabretto
Advisor Pierre-Edouard Portier

Last update : 2016-10-07 10:38:31