On 25 April 2019, we were honored to feature two speakers in our KDD.SG Seminar series and host them in SMU School of Information Systems.
Prof Jie Tang from Tsinghua University summarized several works on using deep learning for deriving graph representations, distilled their fundamental concepts, and described several generalizations and extensions on such models.
In turn, Prof Michalis Vazirgiannis from Ecole Polytechnique described his recent work on using deep learning to derive representations for sets.
The audience was engaged, and the ensuing questions-and-answers were lively with a number of relevant questions. Overall, it was a very informative and inspiring session that certainly amplified our understanding of deep learning and neural networks.