| May 8, 2024 (Wednesday) | |||||||
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| 08:00-17:00 | Registration | ||||||
| 08:30-09:00 | Conference Opening | ||||||
| 09:00-10:00 | Keynote Speech 1 R101 The LLM (Large Language Model) Revolution: Implications from Chatbots and Tool-use to Reasoning (by Dr. Ed H. Chi) |
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| 10:00-10:20 | Coffee Break | ||||||
| 10:20-12:00 | Session 1A R201BC Information Retrieval and Search |
Session 1B R201DE Reinforcement Learning |
Session 1C R101 Graph Neural Networks |
Session 1D R201AF Classification and Clustering |
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| 12:00-13:10 | Lunch | ||||||
| 13:10-15:10 | Industrial Session I R101 |
Session 2A R201BC Graph Learning and Social Networks |
Session 2B R201DE Online, Streaming, and Graph Algorithms |
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| 15:10-15:30 | Coffee Break | ||||||
| 15:30-17:30 |
Industrial Session II |
Session 3A R201BC Deep Learning |
Session 3B R201DE Behavioral Data Mining |
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| Session Name | Paper Information |
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| 1A
Information Retrieval and Search Session Chair: |
DQAC: Detoxifying Query Auto-Completion with Adapters Aishwarya Maheswaran (IIT Hyderabad)*; Kaushal Kumar Maurya (IIT Hyderabad); Manish Gupta (Microsoft,India); Maunendra Sankar Desarkar (IIT Hyderabad) |
| GViG: Generative Visual Grounding using Prompt-based Language Modeling for Visual Question Answering Yi-Ting Li (National Cheng Kung University)*; Ying-Jia Lin (National Cheng Kung University); Chia-Jen Yeh (National Cheng Kung University); ChunYi Lin (NCKU); Hung-Yu Kao (National Cheng Kung University) |
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| Conditional Denoising Diffusion for Sequential Recommendation Yu Wang (UIC)*; Zhiwei Liu (Salesforce); Liangwei Yang (University of Illinois at Chicago); Philip S Yu (UIC) |
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| A New Loss for Image Retrieval: Class Anchor Margin Alexandru Ghita (University of Bucharest); Radu Tudor Ionescu (University of Bucharest)* |
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| Semantic Completion: Enhancing Image-Text Retrieval with Information Extraction and Compression Xue Chen (East China University of Science and Technology)*;Yi Guo (ecust) |
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Interpreting Pretrained Language Models via Concept Bottlenecks |
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| 1B Reinforcement Learning Session Chair: |
Meta-Reinforcement Learning Algorithm Based on Reward and Dynamic Inference Jinhao Chen (Beijing University of Posts and Telecommunications); Chunhong Zhang (Beijing University of Posts and Telecommunications); Zheng Hu (Beijing University of Posts and Telecommunications)* |
| MOT: A Mixture of Actors Reinforcement Learning Method by Optimal Transport for Algorithmic Trading Xi Cheng (Institute of Automation, Chinese Academy of Sciences)*; Jinghao Zhang (CRIPAC, NLPR, CASIA); Yunan Zeng (CASIA); Wenfang Xue (Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Science) |
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| Multi-Agent Reinforcement Learning for Online Placement of Mobile EV Charging Stations Lo Pang-Yun Ting (National Cheng Kung University); Chi-Chun Lin (National Cheng Kung University); Shih-Hsun Lin (National Cheng Kung University); Yu-Lin Chu (National Cheng Kung University); Kun-Ta Chuang (National Cheng Kung University)* |
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| Towards Cost-Efficient Federated Multi-Agent RL with Learnable Aggregation Yi Zhang (The University of Queensland); Sen Wang (The University of Queensland); Zhi Chen (The University of Queensland); Xuwei Xu (The University of Queensland); Stano Funiak (CSIRO); Jiajun Liu (CSIRO)* |
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| Communicative and Cooperative Learning for Multi-agent Indoor Navigation Fengda Zhu (Monash)*; Vincent CS S Lee (Monash University); Rui Liu (University Technology of Sydney) |
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Enhancing Policy Gradient for Traveling Salesman Problem with Data Augmented Behavior Cloning |
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| 1C Graph Neural Networks Session Chair: |
Chaotic Neural Oscillators with Deep Graph Neural Network for Node Classification Le Zhang (BNU-HKBU United International College); Raymond S.T. Lee (Beijing Normal University-Hong Kong Baptist University United International College)* |
| Graph Neural Network Approach to Semantic Type Detection in Tables Ehsan Hoseinzade (Simon Fraser University)*; Ke Wang (SFU) |
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| Alleviating Over-Smoothing via Aggregation over Compact Manifolds Zhou Dongzhuoran (Bosch Center for Artificial Intelligence)*; Hui Yang (Laboratoire Interdisciplinaire des Sciences du Numérique); Bo Xiong (University of Stuttgart); Yue Ma (LRI); Evgeny Kharlamov (Bosch Center for Artificial Intelligence) |
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| Are Graph Embeddings the Panacea? – an Empirical Survey from the Data Fitness Perspective QIANG SUN (University of Western Australia)*; Wei Liu (University of Western Australia); Du Q Huynh (The University of Western Australia); Mark Reynolds (University of Western Australia) |
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Enhancing Network Role Modeling: Introducing Attributed Multiplex Structural Role Embedding for Complex Networks |
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| QWalkVec: Node Embedding by Quantum Walk Rei Sato (KDDI Research, Inc.)*; Shuichiro Haruta (KDDI Research, Inc.); Kazuhiro Saito (KDDI Research, Inc.); Mori Kurokawa (KDDI Research, Inc.) |
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| 1D Classification and Clustering Session Chair: |
AutoClues: Exploring Clustering Pipelines via AutoML and Diversification Matteo Francia (DISI – University of Bologna); Joseph Giovanelli (University of Bologna)*; Matteo Golfarelli (DISI – University of Bologna) |
| ImMC-CSFL: Imbalanced Multi-view Clustering Algorithm Based On Common-Specific Feature Learning Xiaocui Li (Huazhong University of Science and Technology)*; Yu Xiao (Hunan University of Technology and Business); Xinyu Zhang (Hunan University Of Technology and Business); Qingyu Shi (Hunan University of Technology and Business); Xiance Tang (Hunan University Of Technology and Business) |
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| Clustering-friendly Representation Learning for Enhancing Salient Features Toshiyuki Oshima (Toshiba Corporation)*; Kentaro Takagi (Toshiba Corporation); Kouta Nakata (Toshiba Corporation) |
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| Class ratio and its implications for reproducibility and performance in record linkage Jeremy Foxcroft (University of Guelph)*; Luiza Antonie (University of Guelph); Peter Christen (Australian National University) |
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Instance-Ambiguity Weighting for Multi-Label Recognition with Limited Annotations |
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| SEE: Spherical Embedding Expansion for Improving Deep Metric Learning Binh M. Le (Sungkyunkwan University); Simon S Woo (Sungkyunkwan University (SKKU))* |
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| 2A Graph Learning and Social Networks Session Chair: |
Look Around! A Neighbor Relation Graph Learning Framework for Real Estate Appraisal Chih-Chia Li (National Yang Ming Chiao Tung University); Wei-Yao Wang (National Yang Ming Chiao Tung University)*; Wei-Wei Du (Sony); Wen-Chih Peng (NYCU) |
| Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation Jiaqi Wang (Penn State University)*; Yuzhong Chen (Visa research ); Yuhang Wu (Visa Inc.); Mahashweta Das (Visa Research); Hao Yang (Visa Research); Fenglong Ma (Pennsylvania State University) |
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| Improving Structural and Semantic Global Knowledge in Graph Contrastive Learning with Distillation Mi Wen (Shanghai University of Electric Power); Hongwei Wang (Shanghai University of Electirc Power)*; Yunsheng Xue (Shanghai University of Electric Power); Yi Wu (State Grid Shanghai Electric Power Co.,Ltd); Hong Wen (University of Electronic Science and Technology of China) |
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| Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering Siamak Ghodsi (Leibniz University of Hannover; Free University Berlin)*; Seyed Amjad Seyedi (University of Kurdistan); Eirini Ntoutsi (Bundeswehr University Munich) |
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| Quantifying Opinion Rejection: A Method to Detect Social Media Echo Chambers Kushani Perera (University of Melbourne)*; Shanika Karunasekera (The University of Melbourne, Australia) |
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| A Weighted Cross-Modal Feature Aggregation Network for Rumor Detection Jia Li (Guangdong University of Technology)*; Zihan Hu (Guangdong University of Technology); Zhenguo Yang (Guangdong University of Technology); Lap-Kei Lee (Hong Kong Metopolitan University); Fu Lee Wang (Hong Kong Metropolitan University) |
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Exploiting Adaptive Contextual Masking for Aspect-Based Sentiment Analysis |
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| 2B Online, Streaming, and Graph Algorithms Session Chair: |
Streaming Fair $k$-Center Clustering over Massive Dataset with Performance Guarantee Zeyu Lin (Fuzhou University); Longkun Guo (Fuzhou University;Chinese Academy of Sciences Shenzhen Advanced Technology Academe)*; Chaoqi Jia (RMIT University) |
| Adaptive Prediction Interval for Data Stream Regression Yibin Sun (University of Waikato)*; Bernhard Pfahringer (University of Waikato); Albert Bifet (University of Waikato); Heitor M Gomes (Victoria University of Wellington) |
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| DEAL: Data-Efficient Active Learning for regression under drift Bela Hraban Böhnke (Karlsruher Institut für Technologie (KIT))*; Edouard Fouché (Karlsruhe Institute of Technology (KIT)); Klemens Böhm (Karlsruhe Institute of Technology (KIT)) |
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| Lil’HDoC: An Algorithm for Good Arm Identification under Small Threshold Gap Tzu-Hsien Tsai (National Taiwan University); Yun-Da Tsai (National Taiwan University)*; Shou-De Lin (NTU) |
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| Projection-Free Bandit Convex Optimization over Strongly Convex Sets Chenxu Zhang (Zhejiang University); Yibo Wang (Nanjing University); Peng Tian (State Grid Chongqing Electric Power Company); Xiao Cheng (State Grid Chongqing Electric Power Research Institute); Yuanyu Wan (Zhejiang University)*; Mingli Song (Zhejiang University) |
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Leveraging Transfer Learning for Enhancing Graph Optimization Problem Solving |
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| Query-decision Regression between Shortest Path and Minimum Steiner Tree Guangmo Tong (University of Delaware)*; Peng Zhao (University of Delaware); Mina Samizadeh (University of Delaware) |
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| 3A Deep Learning Session Chair: |
LEAF: A Less Expert Annotation Framework with Active Learning Maoliniyazi Aishan (Renmin University)*; Chaohong Ma (Renmin University of China); Yingtao Peng (renmin university of china); Xiaofeng Meng (Renmin University of China) |
| Ranking Enhanced Supervised Contrastive Learning for Regression Ziheng Zhou (Tsinghua University); Ying Zhao (Tsinghua University, China)*; Haojia Zuo (Tsinghua University); Wenguang Chen (Tsinghua University) |
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| Relation-Aware Label Smoothing for Self-KD Jeongho Kim (KAIST); Simon S Woo (Sungkyunkwan University (SKKU))* |
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| Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling Gordon E Moon (Sogang University)*; Bokyeong Yoon (Sogang University); Yoonsang Han (Sogang University) |
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| AdaPQ: Adaptive Exploration Product Quantization with Adversary-aware Block Size Selection Toward Compression Efficiency Yan-Ting Ye (National Taiwan University)*; Ting-An Chen (National Taiwan University); Ming-Syan Chen (National Taiwan University) |
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Adversarial Learning of Group and Individual Fair Representations |
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| LEMT: A Label Enhanced Multi-task Learning Framework for Malevolent Dialogue Response Detection Kaiyue Wang (Soochow University)*; Yang Fan (Soochow University); Yucheng Yao (Soochow University); Xiabing Zhou (Soochow University) |
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| 3B Behavioral Data Mining Session Chair: |
Re-thinking Human Activity Recognition with Hierarchy-aware Label Relationship Modeling Jingwei ZUO (Technology Innovation Institute)*; Hakim Hacid (TII) |
| TFAugment: A Key Frequency-Driven Data Augmentation Method for Human Activity Recognition Hao Zhang (Changsha University of Science and Technology); Bixiao Zeng (University of Chinese Academy of Sciences); Mei Kuang (Changsha University of Science and Technology); Xiaodong Yang (Institute of Computing Technology, Chinese Academy of Sciences)*; Hongfang Gong (Changsha University of Science and Technology) |
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| Improving Knowledge Tracing via Considering Students’ Interaction Patterns Shilong Shu (Nanjing Normal University)*; Liting Wang (Nanjing Normal University); Junhua Tian (Nanjing Normal University) |
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| MDAN: Multi-distribution adaptive networks for LTV prediction Wenshuang Liu (tencent)*; Guoqiang Xu (Tencent); Cunxiang Yin (Tencent); Xinji Luo (tencent) |
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| Improving Anti-Money Laundering via Fourier-based Contrastive Learning Meihan Tong (China National Clearing Center; Tsinghua University)*; Shuai Wang (Hashkey Tech); XinYu Chen (China National Clearing Center); Jinsong Bei (China National Clearing Center) |
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| Learning to Rank Based on Choquet Integral: Application to Association Rules Charles Vernerey (TASC (LS2N-CNRS), IMT Atlantique); Noureddine Aribi (University of Oran); Samir Loudni (TASC (LS2N-CNRS), IMT Atlantique)*; Yahia Lebbah (University Oran1); Nassim Belmecheri (SIMULA) |
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| Agent-based Simulation of Decision-making under Uncertainty to Study Financial Precarity Pegah Nokhiz (Brown University)*; Aravinda Kanchana Ruwanpathirana (University of Utah); Neal Patwari (Washington University in St. Louis); Suresh Venkatasubramanian (Brown University) |
