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COM-621: Advanced Topics in Information Theory

Résumé

The class will focus on information-theoretic progress of the last decade. Topics include: Network Information Theory ; Information Measures: definitions, properties, and applications to probabilistic models.

Séances de cours

Enseignant·e

Michael Christoph Gastpar

Michael Gastpar is a (full) Professor at EPFL. From 2003 to 2011, he was a professor at the University of California at Berkeley, earning his tenure in 2008. He received his Dipl. El.-Ing. degree from ETH Zürich, Switzerland, in 1997 and his MS degree from the University of Illinois at Urbana-Champaign, IL, USA, in 1999. He defended his doctoral thesis at EPFL on Santa Claus day, 2002. He was also a (full) Professor at Delft University of Technology, The Netherlands. His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience. He is a Fellow of the IEEE. He is the co-recipient of the 2013 Communications Society & Information Theory Society Joint Paper Award. He was an Information Theory Society Distinguished Lecturer (2009-2011). He won an ERC Starting Grant in 2010, an Okawa Foundation Research Grant in 2008, an NSF CAREER award in 2004, and the 2002 EPFL Best Thesis Award. He has served as an Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11), and as Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory, Austin, TX.

Source officielle

https://edu.epfl.ch/coursebook/fr/advanced-topics-in-information-theory-COM-621

Page Moodle

http://go.epfl.ch/COM-621

Résumé

Séances de cours

Enseignant·e

Michael Christoph Gastpar

Source officielle

https://edu.epfl.ch/coursebook/fr/advanced-topics-in-information-theory-COM-621

Page Moodle

http://go.epfl.ch/COM-621

Proximité ontologique

Information engineering

Théorie de l'information: Capacité d'un canal

Séances de ce cours (3)

Corrélation maximale : Mesures d'information Connectez-vous à Mediaspace pour regarder cette vidéo

Explore la corrélation maximale dans la théorie de l'information, les propriétés mutuelles de l'information, les mesures de Renyi et les fondements mathématiques de la théorie de l'information.

Théorie avancée de l'information: F-Divergences et erreur de généralisation Connectez-vous à Mediaspace pour regarder cette vidéo

Couvre f-divergences et erreur de généralisation dans la théorie de l'information avancée.

Théorie de l'information avancée: Random Binning Connectez-vous à Mediaspace pour regarder cette vidéo

Explore le binning aléatoire dans la théorie de l'information avancée, en se concentrant sur l'attribution d'étiquettes basées sur la typicité et en atteignant des taux d'erreur négligeables dans le codage source.

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