Table of Contents

• Improving Knowledge Graph Entity Alignment with Graph AugmentationFeng Xie, Xiang Zeng, Bin Zhou 0004, Yusong Tan. 3-14 [doi]
• MixER: MLP-Mixer Knowledge Graph Embedding for Capturing Rich Entity-Relation Interactions in Link PredictionThanh Le 0001, An Pham, Tho Chung, Truong Nguyen, Tuan Nguyen, Bac Le. 15-27 [doi]
• GTEA: Inductive Representation Learning on Temporal Interaction Graphs via Temporal Edge AggregationSiyue Xie, Yiming Li, Da Sun Handason Tam, Xiaxin Liu, Qiufang Ying, Wing Cheong Lau, Dah-Ming Chiu, Shou Zhi Chen. 28-39 [doi]
• You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural NetworkHuaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang. 40-52 [doi]
• UPGAT: Uncertainty-Aware Pseudo-neighbor Augmented Knowledge Graph Attention NetworkYen-Ching Tseng, Zu-Mu Chen, Mi-Yen Yeh, Shou-de Lin. 53-65 [doi]
• Mining Frequent Sequential Subgraph Evolutions in Dynamic Attributed GraphsZhi-cheng, Landy Andriamampianina, Franck Ravat, Jiefu Song, Nathalie Vallès-Parlangeau, Philippe Fournier-Viger, Nazha Selmaoui-Folcher. 66-78 [doi]
• CondTraj-GAN: Conditional Sequential GAN for Generating Synthetic Vehicle TrajectoriesNils Henke, Shimon Wonsak, Prasenjit Mitra, Michael Nolting, Nicolas Tempelmeier. 79-91 [doi]
• A Graph Contrastive Learning Framework with Adaptive Augmentation and Encoding for Unaligned ViewsYifu Guo, Yong Liu. 92-104 [doi]
• MPool: Motif-Based Graph PoolingMuhammad Ifte Khairul Islam, Max Khanov, Esra Akbas. 105-117 [doi]
• Anti-Money Laundering in Cryptocurrency via Multi-Relational Graph Neural NetworkWoochang Hyun, Jaehong Lee, Bongwon Suh. 118-130 [doi]
• CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data Using Normalizing FlowsTri Dung Duong, Qian Li 0003, Guandong Xu. 133-144 [doi]
• Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-outZidi Xiu, Kai-Chen Cheng, David Q. Sun, Jiannan Lu, Hadas Kotek, Yuhan Zhang, Paul McCarthy, Christopher Klein, Stephen Pulman, Jason D. Williams. 145-158 [doi]
• Toward Interpretable Machine Learning: Constructing Polynomial Models Based on Feature Interaction TreesJisoo Jang, Mina Kim, Tien-Cuong Bui, Wen-Syan Li. 159-170 [doi]
• BioSequence2Vec: Efficient Embedding Generation for Biological SequencesSarwan Ali, Usama Sardar, Murray Patterson, Imdadullah Khan. 173-185 [doi]
• Relations Between Adjacency and Modularity Graph PartitioningHansi Jiang, Carl Meyer. 189-200 [doi]
• Bayesian Optimization over Mixed Type Inputs with Encoding MethodsZhihao Liu, Weiming Ou, Songhao Wang. 203-215 [doi]
• Using Flexible Memories to Reduce Catastrophic ForgettingWernsen Wong, Yun Sing Koh, Gillian Dobbie. 219-230 [doi]
• Fair Healthcare Rationing to Maximize Dynamic UtilitiesAadityan Ganesh, Pratik Ghosal, Vishwa Prakash HV, Prajakta Nimbhorkar. 231-242 [doi]
• A Multi-player MAB Approach for Distributed Selection ProblemsJinyu Mo, Hong Xie. 243-254 [doi]
• A Thompson Sampling Approach to Unifying Causal Inference and Bandit LearningHanxuan Xu, Hong Xie. 255-266 [doi]
• Maverick Matters: Client Contribution and Selection in Federated LearningJiyue Huang, Chi Hong, Yang Liu, Lydia Y. Chen, Stefanie Roos. 269-282 [doi]
• pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution ConstraintsYongli Mou, Jiahui Geng, Feng Zhou 0011, Oya Beyan, Chunming Rong, Stefan Decker. 283-294 [doi]
• Inverse Problem of Censored Markov Chain: Estimating Markov Chain Parameters from Censored Transition DataMasahiro Kohjima, Takeshi Kurashima, Hiroyuki Toda. 297-308 [doi]
• Parameter-Free Bayesian Decision Trees for Uplift ModelingMina Rafla, Nicolas Voisine, Bruno Crémilleux. 309-321 [doi]
• Interpretability Meets Generalizability: A Hybrid Machine Learning System to Identify Nonlinear Granger Causality in Global Stock IndicesYixiao Lu, Yokiu Lee, Haoran Feng, Johnathan Leung, Alvin Cheung, Katharina Dost, Katerina Taskova, Thomas Lacombe. 322-334 [doi]
• A Dynamic and Task-Independent Reward Shaping Approach for Discrete Partially Observable Markov Decision ProcessesSepideh Nahali, Hajer Ayadi, Jimmy X. Huang, Esmat Pakizeh, Mir Mohsen Pedram, Leila Safari. 337-348 [doi]
• Multi-Agent Meta-Reinforcement Learning with Coordination and Reward Shaping for Traffic Signal ControlXin Du, Jiahai Wang, Siyuan Chen. 349-360 [doi]
• Regularization of the Policy Updates for Stabilizing Mean Field GamesTalal Algumaei, Ruben Solozabal, Réda Alami, Hakim Hacid, Mérouane Debbah, Martin Takác 0001. 361-372 [doi]
• Constrained Portfolio Management Using Action Space Decomposition for Reinforcement LearningDavid Winkel, Niklas Strauß, Matthias Schubert, Yunpu Ma, Thomas Seidl 0001. 373-385 [doi]
• Transfer Reinforcement Learning Based Negotiating Agent FrameworkSiqi Chen 0001, Tianpei Yang, Heng You, Jianing Zhao, Jianye Hao, Gerhard Weiss 0001. 386-397 [doi]
• A Relational Instance-Based Clustering Method with Contrastive Learning for Open Relation ExtractionXiaoge Li, Dayuan Guo, Tiantian Wang. 401-411 [doi]
• Achieving Provable Byzantine Fault-tolerance in a Semi-honest Federated Learning SettingXingxing Tang, Hanlin Gu, Lixin Fan, Qiang Yang 0001. 415-427 [doi]
• Defending Against Backdoor Attacks by Layer-wise Feature AnalysisNajeeb Moharram Jebreel, Josep Domingo-Ferrer, Yiming Li. 428-440 [doi]
• Enhancing Federated Learning Robustness Using Data-Agnostic Model PruningMark Huasong Meng, Sin G. Teo, Guangdong Bai, Kailong Wang, Jin Song Dong. 441-453 [doi]
• BeamAttack: Generating High-quality Textual Adversarial Examples Through Beam Search and Mixed Semantic SpacesHai Zhu, Qinyang Zhao, Yuren Wu. 454-465 [doi]
• Reduction from Complementary-Label Learning to Probability EstimatesWei-I Lin, Hsuan-Tien Lin. 469-481 [doi]
• Semi-Supervised Text Classification via Self-Paced Semantic-Level ContrastYu Xia, Kai Zhang, Kaijie Zhou, Rui Wang, Xiaohui Hu. 482-494 [doi]
• Multi-Augmentation Contrastive Learning as Multi-Objective Optimization for Graph Neural NetworksXu Li, Yongsheng Chen. 495-507 [doi]
• Adversarial Active Learning with Guided BERT Feature EncodingXiaolin Pang 0001, Kexin Xie, Yuxi Zhang, Max Fleming, Damian Chen Xu, Wei Liu. 508-520 [doi]
• Accelerating Stochastic Newton Method via Chebyshev Polynomial ApproximationFan Sha, Jianyu Pan. 523-534 [doi]
• Stochastic Submodular Maximization via Polynomial EstimatorsGözde Özcan, Stratis Ioannidis. 535-548 [doi]
• Few-Shot Human Motion Prediction for Heterogeneous SensorsRafael Rêgo Drumond, Lukas Brinkmeyer, Lars Schmidt-Thieme. 551-563 [doi]