May 9, 2024 (Thursday)

May 9, 2024 (Thursday)david kang2024-05-03T02:07:38+00:00

May 7, 2024 (Tuesday) May 8, 2024 (Wednesday) May 9, 2024 (Thursday) May 10, 2024 (Friday)

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 R101 (by Prof. Vipin Kumar)
10:00-10:20	Coffee Break
10:20-12:00	Session 4A R201BC Knowledge Graph and Interpretable Data Mining	Session 4B R201DE Semi-supervised and Unsupervised Learning	Session 4C R101 Security, Privacy, and Anomaly Detection	Poster R201AF
12:00-13:10	Lunch
13:10-13:50	Most Influential Paper Award Presentation R101
13:50-17:30	Technical Tour (National Palace Museum)
18:00-21:00	Banquet

Session Name	Paper Information
4A 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)*
4B 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)*
4C 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)