Speaker: Xinyi Gao
This comprehensive experimental study demonstrates that SNS consistently outperforms existing methods in different benchmark datasets.
Speaker: Hechuan Wen
Causal inference is increasingly important in guiding decision-making in high-stake domains, such as healthcare, education, e-commerce, etc.
Speaker: Dr Shoujin Wang (University of Technology Sydney)
In recent years, sequential/session-based recommendations have emerged as a new recommendation paradigm to well model users’ dynamic and short-term preferences for more accurate and timely recommendations.
Speaker: Andrea Parker, Growth ML Engineer (Weights & Biases)
Join us to learn all about experiment tracking at scale with Pachyderm and Weights & Biases.
Speaker: Dr Grace Hui Yang (Georgetown University)
We propose a novel SEgment-based Neural Indexing method, SEINE, which provides a general indexing framework that can flexibly support a variety of interaction-based neural retrieval methods.
Speaker: Prof Stefan Böttcher - Universität Paderborn (Germany)
This talk gives an overview of the key ideas behind grammar-based compression techniques for strings, trees, and graphs.
Speaker: Dr Ziran Wang (Purdue University)
In this talk, a Mobility Digital Twin (MDT) framework is introduced, which is defined as an Artificial Intelligence (AI)-based data-driven cloud-edge-device framework for mobility services.
Speaker: Dr Shixun Huang (RMIT University)
In this talk, recent advances under multiple fields (i.e., data mining, viral marketing and urban computing) of graph analytics will be introduced.
