Deep Recommendations for e-Commerce

E-commerce is a very dynamic field where user behaviour is crucial for deriving personalized suggestions. This talk is a high-level overview of how Meta incorporates this behaviour by using deep learning towards better recommendations for Shops.
 

Georgios is a machine learning engineer at Meta London, focusing on recommender systems, while he also worked on natural language processing. He received his Ph.D. from EPFL in September 2020, where he worked under the supervision of Rachid Guerraoui. Before joining EPFL, he received his MEng in Electrical and Computer Engineering from NTUA. His research focus is on distributed machine learning techniques that are privacy-preserving and robust against arbitrary failures (such as adversarial attacks). He is mainly a practitioner but also studies algorithmic tools from a theoretical perspective. His work has led to publications in multiple premier conferences such ICML and AAAI while he has also won several awards including the EPFL Ph.D. fellowship and the best paper award in Middleware 2020. More about Georgios: https://gdamaskinos.com/