Καλημέρα σας,
την ερχόμενη Τρίτη θα έχουμε τη χαρά να φιλοξενήσουμε στο κτίριο της Αθήνας τον Δρ. Δημήτρη Δημητριάδη, Principal Appied Scientist at Amazon, που θα μας μιλήσει για:
"Federated Learning: New Approaches in Learning and Applications to Lifelong Learning"
Abstract: New demands in data management are emerging nowadays. Some of these constraints are driven by the need for privacy compliance of the personal data and some of them by the need to train bigger, better, faster models. As such, increasingly more data is stored behind inaccessible firewalls or on users' devices without the option of sharing for centralized training. To this end, the Federated Learning (FL) paradigm has been proposed, addressing the privacy concerns, while still processing such inaccessible data in a continual manner. However, FL doesn't come as a free lunch and new technical challenges havε emerged. Herein, we will present some new ways of addressing such challenges while federating heterogeneous models, dealing with the dynamic nature of learning or in applications such as wakeword detection.
Και λίγα περισσότερα λόγια για τον Δρ. Δημήτρη Δημητριάδη:
Dr. D. Dimitriadis is Principal Applied Scientist in Amazon, where he is currently the technical lead for Federated Learning and Analytics across the company, Continual and Semi-supervised Learning. He has worked in Microsoft Research, IBM Research and AT&T Labs (2009-14), lecturer P.D 407/80 at the School of ECE, NTUA, Greece. He is a Senior Member of IEEE and has served as a chair in several conferences and workshops. He has published more than 100 papers in peer-reviewed scientific journals and conferences with 3000 citations. He received his PhD degree from NTUA in February 2005. His PhD Thesis Title is "Non-Linear Speech Processing, Modulation Models and Applications to Speech Recognition".
Η παρουσίαση θα γίνει στην Αίθουσα Zampolli και θα μεταδοθεί και διαδικτυακά.
Σας περιμένουμε,
Νάσος
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