Recap on CS Seminar Series 2: An Introduction to Neural Recommender Models
On the first Sunday of 2019, 6Estates held the second CS Seminar at BLOCK71 Singapore. CS Seminar is an initiative by 6Estates to facilitate the sharing of technical knowledge by academics and industry experts, to promote AI & Computer Science community in Singapore.
We invited Dr He Xiangnan as our guest speaker. He is a senior research fellow at School of Computing, National University of Singapore. His research interests span recommender systems, information retrieval, and multi-media processing. He has over 50 publications appeared in several top conferences such as SIGIR, WWW, MM, and IJCAI, and journals including TKDE, TOIS, and TMM.
In this talk, Dr. He briefly introduced traditional recommendation techniques and emphasised on the emerging neural recommender models. He covered several advances on feature representation learning models, feature interaction learning models, and adversarial training method.
Recommendation systems play a vital role in online information systems and are a major monetisation tool for user-oriented platforms. Recently, there has been an increasing research interest in recommendation technology, and significant progress has been made owing to the fast development of neural network techniques.