The School of Computing and Data Science (https://www.cds.hku.hk/) was established by the University of Hong Kong on 1 July 2024, comprising the Department of Computer Science and Department of Statistics and Actuarial Science.

Advanced Topics in Graph Representation Learning
Advanced Topics in Graph Representation Learning

20220223 seminar banner

The Department of Computer Science is pleased to announce the following interesting mini lecture series to be given by Dr. Chao Huang in February - April 2022. All CS RPg students and senior undergraduate students are welcome to join.

 

Title: Advanced Topics in Graph Representation Learning
Speaker: Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU
Period: February 23 - April 6, 2022 (Wednesday) (total 5 lectures, see detailed schedule below)
Time: 2:00 pm - 3:00 pm
Venue: Online via Zoom (Registration is required - by invitation)

 

Description:
Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

 

About the Speaker:
Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.

 

Schedule and topics:

Lecture 1:
February 23, 2022 (Wed)

Introduction of graph mining;
Core concepts of graph representation learning/network embedding;
Heterogeneous graph analysis

Lecture 2:
March 2, 2022 (Wed)

Graph neural networks (GNN)/GNN-based applications/self-supervised graph learning

Lecture 3:
March 23, 2022 (Wed)

Recommendation with graphs I;
Social and knowledge-aware recommender systems/user personalization

Lecture 4:
March 30, 2022 (Wed)

Recommendation with graphs II;
Recommendation with behavior heterogeneity and diversity

Lecture 5:
April 6, 2022 (Wed)

Graph-based spatial-temporal learning for smart cities

 

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香港大學計算機科學系
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