May 9, 2024 (Thursday)
08:00-17:00 Registration
09:00-10:00 Keynote Speech 2
Knowledge-Guided Machine Learning: A New Framework for Accelerating Scientific Discovery and Addressing Global Environmental Challenges
(by Prof. Vipin Kumar)
10:00-10:20 Coffee Break
10:20-12:00 Session 4A
Knowledge Graph and Interpretable Data Mining
Session 4B
Semi-supervised and Unsupervised Learning
Session 4C
Security, Privacy, and Anomaly Detection
12:00-13:10 Lunch
13:10-13:50 Most Influential Paper Award Presentation
13:50-17:30 Technical Tour
(National Palace Museum)


Session Name Paper Information
Knowledge Graph and Interpretable Data Mining

Session Chair:
Kushani Perera
(University of Melbourne)

Two-Stage Knowledge Graph Completion based on Semantic Features and High-Order Structural Features
Shimei Luo (Tianjin University)*
SemPool: Simple, robust, and interpretable KG pooling for enhancing language models
Costas Mavromatis (University of Minnesota)*; Petros K Karypis (UC San Diego); George Karypis (University of Minnesota, Twin Cities)
RouteExplainer: An Explanation Framework for Vehicle Routing Problem
Daisuke Kikuta (NTT Corporation)*; Hiroki Ikuchi (NTT Corporation); Kengo Tajiri (NTT Corporation); Yuusuke Nakano (NTT)
Random Mask Perturbation Based Explainable Method of Graph Neural Networks
Xinyue Yang (Beijing University of Posts and Telecommunications); Hai Huang (Beijing University of Posts and Telecommunications)*; Xingquan Zuo (Beijing University of Posts and Telecommunications)

On the efficient Explanation of Outlier Detection Ensembles through Shapley Values
Simon Klüttermann (TU Dortmund)*; Chiara Balestra (TU Dortmund); Emmanuel Müller (TU Dortmund)

Towards Nonparametric Topological Layers in Neural Networks
Gefei Shen (University of Washingtong); Dongfang Zhao (University of Washington)*
Semi-supervised and Unsupervised Learning

Session Chair:
Chih-Ya Shen
(National Tsing Hua University)

SAWTab: Smoothed Adaptive Weighting for Tabular Data in Semi-Supervised Learning
Morteza Mohammady Gharasuie (Old Dominion University)*; Fengjiao Wang (University of Utah); Omar Sharif (Old Dominion University); Ravi Mukkamala (Old Dominion University)
Accurate Semi-supervised Automatic Speech Recognition via Multi-hypotheses-based Curriculum Learning
Junghun Kim (Seoul National University); Ka Hyun Park (Seoul National University); U Kang (Seoul National University)*
IR Embedding Fairness Inspection via Contrastive Learning and Human-AI Collaborative Intelligence
Heng Huang (Xiaohongshu)*; Yunhan Bai (Xiaohongshu); Hongwei Liang (Xiaohongshu); Xiaozhong Liu (Worcester Polytechnic Institute)
DALLMi: Domain Adaption for LLM-based Multi-label Classifier
Miruna L Betianu (TU Delft); Marco Aldinucci (University of Turin); Robert Birke (University of Torino); Lydia Chen (TU Delft)*; Abele Mălan (TU Delft)
Modeling Treatment Effect with Cross-Domain Data
Bin Han (Ant Group); Ya-Lin Zhang (Ant Group)*; Lu Yu (Ant Group); Biying Chen (Ant Group); Longfei Li (Ant Financial Services Group ); Jun Zhou (Ant Services Group)

Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum
Hanbing Liu (Tsinghua University); Jingge Wang (Tsinghua University); Xuan Zhang (Tsinghua University); Ye Guo (Tsinghua Shenzhen International Graudate School); Yang Li (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University)*

Security, Privacy, and Anomaly Detection

Session Chair:
Simon S. Woo
(Sungkyunkwan University, S. Korea)

Backdoor Attack against One-Class Sequential Anomaly Detection Models
He Cheng (Utah State University)*; Shuhan Yuan (Utah State University)
Multi-Task Contrastive Learning for Anomaly Detection on Attributed Networks
Junjie Zhang (Harbin Institute of Technology, Shenzhen)*; Yuxin Ding (Harbin Institute of Technolgoy (Shenzhen))
MSTAN: A Multi-view Spatio-Temporal Aggregation Network Learning Irregular Interval User Activities for Fraud Detection
Wenbo Zhang (Harbin Institute of Technology (Shenzhen)); Shuo Zhang (HIT); Xingbang Hu (Harbin Institute of Technology (Shenzhen)); Hejiao Huang (Harbin Institute of Technology (Shenzhen))*
Bi-CryptoNets: Leveraging Different-Level Privacy for Encrypted Inference
Man-Jie Yuan (Nanjing University)*; Zheng Zou (School of Artificial Intelligence, Nanjing University); Wei Gao (Nanjing University)
SASBO: Sparse Attack via Stochastic Binary Optimization
Yihan Meng (Department of Computer Science and Technology, Nanjing University, Nanjing 210023, China)*; Weitao Li (Department of Computer Science and Technology, Nanjing University, Nanjing 210023, China); Lin Shang (Nanjing University)
SD-Attack: Targeted Spectral Attacks on Graphs
Xianren Zhang (University of Cincinnati)*; Jing Ma (Case Western Reserve University); Yushun Dong (University of Virginia); Chen Chen (University of Virginia); Min Gao (Chongqing University); Jundong Li (University of Virginia)