| 2023 | A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder. Zheng Liu, Xiaohan Li, Philip S. Yu |
| 2023 | A Deep Reinforcement Learning Approach to Configuration Sampling Problem. Amir Abolfazli, Jakob Spiegelberg, Gregory Palmer, Avishek Anand |
| 2023 | A Graph Convolutional Neural Network for Recommendation Based on Community Detection and Combination of Multiple Heterogeneous Graphs. Caihong Mu, Heyuan Huang, Yunfei Fang, Yi Liu |
| 2023 | A Mixed-State Streaming Edge Partitioning based on Combinatorial Design. Zhenyu Zhang, Wenwen Qu, Weixi Zhang, Junlin Shang, Xiaoling Wang |
| 2023 | A Practical Clean-Label Backdoor Attack with Limited Information in Vertical Federated Learning. Peng Chen, Jirui Yang, Junxiong Lin, Zhihui Lu, Qiang Duan, Hongfeng Chai |
| 2023 | A Progressive Sampling Method for Dual-Node Imbalanced Learning with Restricted Data Access. Yixuan Qiu, Weitong Chen, Miao Xu |
| 2023 | A Symbolic Representation of Two-Dimensional Time Series for Arbitrary Length DTW Motif. Makoto Imamura, Takaaki Nakamura |
| 2023 | A TSICN-based Inferential Synthesis Method for Class Imbalance in Credit Scoring. Dongxu Fan, Xuanzhi Feng, Jinghe Jiang, Yuming Jiang, Le Zhang, Dasha Hu |
| 2023 | ATTA: Adversarial Task-transferable Attacks on Autonomous Driving Systems. Qingjie Zhang, Maosen Zhang, Han Qiu, Tianwei Zhang, Mounira Msahli, Gérard Memmi |
| 2023 | Adaptive Student Inference Network for Efficient Single Image Super-Resolution. Kang Miao, Zhao Zhang, Jiahuan Ren, Mingbo Zhao, Haijun Zhang, Richang Hong |
| 2023 | An Impact Study of Concept Drift in Federated Learning. Guanhui Yang, Xiaoting Chen, Tengsen Zhang, Shuo Wang, Yun Yang |
| 2023 | Answering Subjective Induction Questions on Products by Summarizing Multi-sources Multi-viewpoints Knowledge. Yufeng Zhang, Mengxiang Wang, Jianxing Yu |
| 2023 | Anti-Noise Muiti-View Feature Selection With Sample Constraints. Jiaye Li, Hang Xu, Hao Yu, Weixin Li, Shichao Zhang |
| 2023 | Attacking c-MARL More Effectively: A Data Driven Approach. Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng |
| 2023 | Auto Graph Filtering for Bundle Recommendation. Xiang-Long Li, Wu-Dong Xi, Xing-Xing Xing, Chang-Dong Wang |
| 2023 | BDVFL: Blockchain-based Decentralized Vertical Federated Learning. Shuo Wang, Keke Gai, Jing Yu, Liehuang Zhu |
| 2023 | Backdoor Attack on 3D Grey Image Segmentation. Honghui Xu, Zhipeng Cai, Zuobin Xiong, Wei Li |
| 2023 | Balancing Summarization and Change Detection in Graph Streams. Shintaro Fukushima, Kenji Yamanishi |
| 2023 | Balancing and Contrasting Biased Samples for Debiased Visual Question Answering. Runlin Cao, Zhixin Li |
| 2023 | Bayesian A/B Testing with Covariates. Yuanyu Zhang, Cheng Qian, Wenhang Bao |
| 2023 | Beyond Discrete Selection: Continuous Embedding Space Optimization for Generative Feature Selection. Meng Xiao, Dongjie Wang, Min Wu, Pengfei Wang, Yuanchun Zhou, Yanjie Fu |
| 2023 | Beyond Lexical Consistency: Preserving Semantic Consistency for Program Translation. Yali Du, Yi-Fan Ma, Zheng Xie, Ming Li |
| 2023 | Bilateral Sequential Hypergraph Convolution Network for Reciprocal Recommendation. Jiaxing Chen, Hongzhi Liu, Hongrui Guo, Yingpeng Du, Zekai Wang, Yang Song, Zhonghai Wu |
| 2023 | Boosting Urban Prediction via Addressing Spatial-Temporal Distribution Shift. Xuanming Hu, Wei Fan, Kun Yi, Pengfei Wang, Yuanbo Xu, Yanjie Fu, Pengyang Wang |
| 2023 | CAC: Enabling Customer-Centered Passenger-Seeking for Self-Driving Ride Service with Conservative Actor-Critic. Palawat Busaranuvong, Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo |
| 2023 | CVaDeS: A Conditional Variational Deep Survival Model for Survival Analysis. Jinyuan Luo, Zikai Xiao, Wen Shi, Linhai Xie, Hong Yang, Xiaoxia Yin, Yanchun Zhang |
| 2023 | CaT: Balanced Continual Graph Learning with Graph Condensation. Yilun Liu, Ruihong Qiu, Zi Huang |
| 2023 | Can Neural Networks Distinguish High-school Level Mathematical Concepts? Sebastian Wankerl, Andrzej Dulny, Gerhard Götz, Andreas Hotho |
| 2023 | Cascaded Cross Attention for Review-based Sequential Recommendation. Bingsen Huang, Jinwei Luo, Weihao Du, Weike Pan, Zhong Ming |
| 2023 | Causal Discovery by Continuous Optimization with Conditional Independence Constraint: Methodology and Performance. Yewei Xia, Hao Zhang, Yixin Ren, Jihong Guan, Shuigeng Zhou |
| 2023 | Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing. Moyu Zhang, Xinning Zhu, Chunhong Zhang, Feng Pan, Wenchen Qian, Hui Zhao |
| 2023 | Collaborative Word-based Pre-trained Item Representation for Transferable Recommendation. Shenghao Yang, Chenyang Wang, Yankai Liu, Kangping Xu, Weizhi Ma, Yiqun Liu, Min Zhang, Haitao Zeng, Junlan Feng, Chao Deng |
| 2023 | Compatible Transformer for Irregularly Sampled Multivariate Time Series. Yuxi Wei, Juntong Peng, Tong He, Chenxin Xu, Jian Zhang, Shirui Pan, Siheng Chen |
| 2023 | Computing Marginal and Conditional Divergences between Decomposable Models with Applications. Loong Kuan Lee, Geoffrey I. Webb, Daniel F. Schmidt, Nico Piatkowski |
| 2023 | Concentric Ring Loss for Face Forgery Detection. Yu Yin, Yue Bai, Yizhou Wang, Yun Fu |
| 2023 | Concordance Learning with Spectral Decay on Triplet Similarity. Jiansheng Fang, Jiajian Li |
| 2023 | ContRE: A Complementary Measure for Robustness Evaluation of Deep Networks via Contrastive Examples. Xuhong Li, Xuanyu Wu, Linghe Kong, Xiao Zhang, Siyu Huang, Dejing Dou, Haoyi Xiong |
| 2023 | Context Does Matter: End-to-end Panoptic Narrative Grounding with Deformable Attention Refined Matching Network. Yiming Lin, Xiao-Bo Jin, Qiufeng Wang, Kaizhu Huang |
| 2023 | Context Sketching for Memory-efficient Graph Representation Learning. Kai-Lang Yao, Wu-Jun Li |
| 2023 | Contextual Target-Specific Stance Detection on Twitter: Dataset and Method. Yupeng Li, Dacheng Wen, Haorui He, Jianxiong Guo, Xuan Ning, Francis C. M. Lau |
| 2023 | Continual Semantic Segmentation via Scalable Contrastive Clustering and Background Diversity. Qi Yang, Xing Nie, Linsu Shi, Jiazhong Yu, Fei Li, Shiming Xiang |
| 2023 | Continual Trajectory Prediction with Uncertainty-Aware Generative Memory Replay. Xiushi Feng, Shuncheng Liu, Haitian Chen, Kai Zheng |
| 2023 | Contrastive Learning-based Multi-behavior Recommendation with Semantic Knowledge Enhancement. Wenxuan Yu, Chenzhong Bin, Wenqiang Liu, Liang Chang |
| 2023 | ConvAOA: A Convolutional Attention Over Attention Model for Click-Through Rate Prediction. Bin Yang, Tianmu Sha, Ying Xing, Ziyang Wang, Zhipu Xie, Xin Wang |
| 2023 | CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation. Jun Wang, Haoxuan Li, Chi Zhang, Dongxu Liang, Enyun Yu, Wenwu Ou, Wenjia Wang |
| 2023 | Counterfactual Explanations for Time Series Forecasting. Zhendong Wang, Ioanna Miliou, Isak Samsten, Panagiotis Papapetrou |
| 2023 | DSG: An End-to-End Document Structure Generator. Johannes Rausch, Gentiana Rashiti, Maxim Gusev, Ce Zhang, Stefan Feuerriegel |
| 2023 | Data Quality Aware Hierarchical Federated Reinforcement Learning Framework for Dynamic Treatment Regimes. Mingyi Li, Xiao Zhang, Haochao Ying, Yang Li, Xu Han, Dongxiao Yu |
| 2023 | Decision-focused Graph Neural Networks for Graph Learning and Optimization. Yang Liu, Chuan Zhou, Peng Zhang, Shuai Zhang, Xiaoou Zhang, Zhao Li, Hongyang Chen |
| 2023 | Deep Multi-kernel Clustering Network. Lina Ren, Ruizhang Huang, Shengwei Ma, Yongbin Qin, Yanping Chen, Chuan Lin |
| 2023 | Deep Optimal Isolation Forest with Genetic Algorithm for Anomaly Detection. Haolong Xiang, Xuyun Zhang, Mark Dras, Amin Beheshti, Wanchun Dou, Xiaolong Xu |
| 2023 | DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing. Li Sun, Zhenhao Huang, Hua Wu, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu |
| 2023 | Device-Unimodal Cloud-Multimodal Collaboration for Livestreaming Content Understanding. Yufei Zhu, Chaoyue Niu, Yikai Yan, Zhijie Cao, Hao Jiang, Chengfei Lyu, Shaojie Tang, Fan Wu |
| 2023 | DiffNAS: Bootstrapping Diffusion Models by Prompting for Better Architectures. Wenhao Li, Xiu Su, Shan You, Fei Wang, Chen Qian, Chang Xu |
| 2023 | Differentiable Bayesian Structure Learning with Acyclicity Assurance. Quang-Duy Tran, Phuoc Nguyen, Bao Duong, Thin Nguyen |
| 2023 | Dimensionality and Curvature Selection of Graph Embedding using Decomposed Normalized Maximum Likelihood Code-Length. Ryo Yuki, Atsushi Suzuki, Kenji Yamanishi |
| 2023 | Discovering Protein Interactions and Repurposing Drugs in SARS-CoV-2 (COVID-19) via Learning on Robust Multipartite Graphs. Xiangyu Li, Armand Ovanessians, Hua Wang |
| 2023 | Discovering the Cognition behind Language: Financial Metaphor Analysis with MetaPro. Rui Mao, Kelvin Du, Yu Ma, Luyao Zhu, Erik Cambria |
| 2023 | Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference. Debo Cheng, Yang Xie, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Yinghao Zhang, Zaiwen Feng |
| 2023 | Distribution-Based Trajectory Clustering. Zijing Wang, Ye Zhu, Kai Ming Ting |
| 2023 | Distributional Cloning for Stabilized Imitation Learning via ADMM. Xin Zhang, Yanhua Li, Ziming Zhang, Christopher G. Brinton, Zhenming Liu, Zhi-Li Zhang |
| 2023 | Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation. Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao |
| 2023 | Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation. Qiaoyu Tan, Daochen Zha, Ninghao Liu, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu |
| 2023 | Early Spatiotemporal Event Prediction via Adaptive Controller and Spatiotemporal Embedding. Wei Shao, Ziyan Peng, Yufan Kang, Xiao Xiao, Zhiling Jin |
| 2023 | Efficient Cardinality and Cost Estimation with Bidirectional Compressor-based Ensemble Learning. Zibo Liang, Xu Chen, Yan Zhao, Jiandong Xie, Kai Zeng, Kai Zheng |
| 2023 | Efficient Multi-source Contact Event Query Processing for Moving Objects. Pengyue Li, Hua Dai, Yu Chen, Bohan Li, Geng Yang |
| 2023 | Efficient and Effective Entity Alignment for Evolving Temporal Knowledge Graphs. Yunfei Li, Lu Chen, Chengfei Liu, Rui Zhou, Jianxin Li |
| 2023 | Enhancing Bug Localization through Bug Report Summarization. Xia Zhang, Ziye Zhu, Yun Li |
| 2023 | Enhancing GNN-based Fraud Detector via Semantic Extraction and Max-Representation-Margin. Bingzhe Zhang, Xinye Wang, Zhenyang Yu, Yuanhao Zhang, Chengxin He, Song Deng, Zhaohang Luo, Lei Duan |
| 2023 | Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, Zibin Zheng |
| 2023 | Enhancing Personalized Healthcare via Capturing Disease Severity, Interaction, and Progression. Yanchao Tan, Zihao Zhou, Leisheng Yu, Weiming Liu, Chaochao Chen, Guofang Ma, Xiao Hu, Vicki Stover Hertzberg, Carl Yang |
| 2023 | Enhancing Social Recommendation with Multi-View BERT Network. Tushar Prakash, Raksha Jalan, Naoyuki Onoe |
| 2023 | Enriched Representation Learning for Longitudinal Chest X-ray Analysis: A Novel Approach for Improved Disease Detection and Localization. Xiangyu Li, Armand Ovanessians, Hua Wang |
| 2023 | Entropy Aware Training for Fast and Accurate Distributed GNN. Dhruv Deshmukh, Gagan Raj Gupta, Manisha Chawla, Vishwesh Jatala, Anirban Haldar |
| 2023 | Equipping Federated Graph Neural Networks with Structure-aware Group Fairness. Nan Cui, Xiuling Wang, Wendy Hui Wang, Violet Xinying Chen, Yue Ning |
| 2023 | Evading Deep Learning-Based Malware Detectors via Obfuscation: A Deep Reinforcement Learning Approach. Brian Etter, James Lee Hu, Mohammadreza Ebrahimi, Weifeng Li, Xin Li, Hsinchun Chen |
| 2023 | Exact-Fun: An Exact and Efficient Federated Unlearning Approach. Zuobin Xiong, Wei Li, Yingshu Li, Zhipeng Cai |
| 2023 | Explainable Adaptive Tree-based Model Selection for Time-Series Forecasting. Matthias Jakobs, Amal Saadallah |
| 2023 | Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness. Yanzhao Wu, Ka Ho Chow, Wenqi Wei, Ling Liu |
| 2023 | FASM and FAST-YB: Significant Pattern Mining with False Discovery Rate Control. Paolo Pellizzoni, Karsten M. Borgwardt |
| 2023 | FM-IGNN: Interaction Graph Neural Network with Fine-grained Matching for Session-based Recommendation. Zongzhi Han, Zhonghong Ou, Yifan Zhu, Xiaodong Li, Meina Song |
| 2023 | Fact-Preserved Personalized News Headline Generation. Zhao Yang, Junhong Lian, Xiang Ao |
| 2023 | Fast Multi-Modal Multi-Instance Support Vector Machine for Fine-grained Chest X-ray Recognition. Hoon Seo, Hua Wang |
| 2023 | Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution. Yawei Li, Zhao Zhang, Suiyi Zhao, Jicong Fan, Haijun Zhang, Mingliang Xu |
| 2023 | Fed-mSSA: A Federated Approach for Spatio-Temporal Data Modeling Using Multivariate Singular Spectrum Analysis. Jiayu He, Matloob Khushi, Tung-Anh Nguyen, Nguyen Hoang Tran |
| 2023 | FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization. Qianyu Long, Christos Anagnostopoulos, Shameem Puthiya Parambath, Daning Bi |
| 2023 | Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao |
| 2023 | Federated Learning for Privacy-Preserving Prediction of Occupational Group Mobility Using Multi-Source Mobile Data. Hao Li, Hao Jiang, Haoran Xian, Qimei Chen |
| 2023 | Feedback Decision Transformer: Offline Reinforcement Learning With Feedback. Liad Giladi, Gilad Katz |
| 2023 | Fine-grained Urban Flow Inference with Unobservable Data via Space-Time Attraction Learning. Ruifeng Wang, Yuansheng Liu, Yongshun Gong, Wei Liu, Meng Chen, Yilong Yin, Yu Zheng |
| 2023 | GAFNO: Gated Adaptive Fourier Neural Operator for Task-Agnostic Time Series Modeling. Xin-Yi Li, Yu-Bin Yang |
| 2023 | GCFormer: Granger Causality based Attention Mechanism for Multivariate Time Series Anomaly Detection. Shiwang Xing, Jianwei Niu, Tao Ren |
| 2023 | GMMDA: Gaussian Mixture Modeling of Graph in Latent Space for Graph Data Augmentation. Yanjin Li, Linchuan Xu, Kenji Yamanishi |
| 2023 | GeoMixer: The MLP-Based Sequential POI Recommender with Travel Routing Modelling. Tianxing Wang, Can Wang, Hui Tian, Hong Shen |
| 2023 | Graph Collaborative Optimization for Sequential Recommendation. Chunjing Xiao, Yan Shen, Yuxiang Zhang, Shijie Li |
| 2023 | Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering. Ke Xu, Yuanjie Zhu, Weizhi Zhang, Philip S. Yu |
| 2023 | Graph Open-Set Recognition via Entropy Message Passing. Lina Yang, Bin Lu, Xiaoying Gan |
| 2023 | Graph Reciprocal Neural Networks by Abstracting Node as Attribute. Liang Yang, Jiayi Wang, Dongxiao He, Chuan Wang, Xiaochun Cao, Bingxin Niu, Zhen Wang |
| 2023 | Graph Sampling based Fairness-aware Recommendation over Sensitive Attribute Removal. Shenghao Liu, Guoyang Wu, Xianjun Deng, Hongwei Lu, Bang Wang, Laurence T. Yang, James J. Park |
| 2023 | Graph Self-Contrast Representation Learning. Minjie Chen, Yao Cheng, Ye Wang, Xiang Li, Ming Gao |
| 2023 | HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. Minh-Hao Van, Alycia N. Carey, Xintao Wu |
| 2023 | Handling New Class in Online Label Shift. Yu-Yang Qian, Yong Bai, Zhen-Yu Zhang, Peng Zhao, Zhi-Hua Zhou |
| 2023 | Heterogeneous Treatment Effect Estimation with Subpopulation Identification for Personalized Medicine in Opioid Use Disorder. Seungyeon Lee, Ruoqi Liu, Wenyu Song, Ping Zhang |
| 2023 | Hierarchical Context Modeling Network for Landmark Recognition. Xing Bao, Huan Zheng, Zhao Zhang, Zhengjun Zha, Meng Wang |
| 2023 | Hierarchical Graph Contrastive Learning via Debiasing Noise Samples with Adaptive Repelling Ratio. Peishuo Liu, Cangqi Zhou, Jing Zhang, Qianmu Li, Dianming Hu |
| 2023 | Hierarchical Label Inference Incorporating Attribute Semantics in Attributed Networks. Junliang Li, Yajun Yang, Qinghua Hu, Xin Wang, Hong Gao |
| 2023 | Homogeneous Entity Context Enhanced Representation Network for Temporal Knowledge Graph Reasoning. Yujia Yang, Conghui Zheng, Li Pan |
| 2023 | Hypergraph Attribute Attention Network for Community Recommendation. Kang Li, Wu-Dong Xi, Xing-Xing Xing, Chang-Dong Wang |
| 2023 | Hypergraph Contrastive Learning for Drug Trafficking Community Detection. Tianyi Ma, Yiyue Qian, Chuxu Zhang, Yanfang Ye |
| 2023 | IE-Evo: Internal and External Evolution-Enhanced Temporal Knowledge Graph Forecasting. Kangzheng Liu, Feng Zhao, Guandong Xu, Shiqing Wu |
| 2023 | IEEE International Conference on Data Mining, ICDM 2023, Shanghai, China, December 1-4, 2023 Guihai Chen, Latifur Khan, Xiaofeng Gao, Meikang Qiu, Witold Pedrycz, Xindong Wu |
| 2023 | IKGN: Intention-aware Knowledge Graph Network for POI Recommendation. Xiaoyu Zhu, Chenyang Bu, Bingbing Dong, Shengwei Ji, Yi He, Xindong Wu |
| 2023 | Infinitely Deep Graph Transformation Networks. Lei Zhang, Qisheng Zhang, Zhiqian Chen, Yanshen Sun, Chang-Tien Lu, Liang Zhao |
| 2023 | Insight Analysis for Tennis Strategy and Tactics. Zhaoyu Liu, Kan Jiang, Zhe Hou, Yun Lin, Jin Song Dong |
| 2023 | Interactive Activities Initiation through Retrieving Hidden Social Information Networks. YuLong Song, Bin Fu, Jianxiong Guo, Xiaofeng Gao |
| 2023 | Interpretable Subgraph Feature Extraction for Hyperlink Prediction. Peiyan Li, Liming Pan, Kai Li, Claudia Plant, Christian Böhm |
| 2023 | Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling. Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar |
| 2023 | Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation. Xurong Liang, Tong Chen, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin |
| 2023 | Learning Efficient Unsupervised Satellite Image-based Building Damage Detection. Yiyun Zhang, Zijian Wang, Yadan Luo, Xin Yu, Zi Huang |
| 2023 | Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. Oren Barkan, Yuval Asher, Amit Eshel, Yehonatan Elisha, Noam Koenigstein |
| 2023 | Leveraging Data Density and Sparsity for Efficient SVM Training on GPUs. Borui Xu, Zeyi Wen, Lifeng Yan, Zhan Zhao, Zekun Yin, Weiguo Liu, Bingsheng He |
| 2023 | Limitations of Perturbation-based Explanation Methods for Temporal Graph Neural Networks. Minh N. Vu, My T. Thai |
| 2023 | Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help? Ngoc Dang Nguyen, Wei Tan, Lan Du, Wray L. Buntine, Richard Beare, Changyou Chen |
| 2023 | MCRec: Multi-channel Gated Gifts Recommendation. Ting-Ting Su, Wu-Dong Xi, Xing-Xing Xing, Chang-Dong Wang |
| 2023 | MEG: Masked Ensemble Tabular Data Generator. Yishuo Zhang, Nayyar Abbas Zaidi, Gang Li, Wray L. Buntine |
| 2023 | MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale. Yuchen Li, Haoyi Xiong, Linghe Kong, Zeyi Sun, Hongyang Chen, Shuaiqiang Wang, Dawei Yin |
| 2023 | MPRE: Multi-perspective Patient Representation Extractor for Disease Prediction. Ziyue Yu, Jiayi Wang, Wuman Luo, Rita Tse, Giovanni Pau |
| 2023 | MTT-DynGL: Towards Multidimensional Topology-oriented Time-series Dynamic Graphs Learning Model. Chen Shi, Yujie Mao, Yiding Shen, Wenli Xiong, Feng Liu, Chenhui Li, Changbo Wang |
| 2023 | Matching Words for Out-of-distribution Detection. Keke Tang, Xujian Cai, Weilong Peng, Daizong Liu, Peican Zhu, Pan Zhou, Zhihong Tian, Wenping Wang |
| 2023 | Matrix Profile XXIX: C Sadaf Tafazoli, Yue Lu, Renjie Wu, Thirumalai Vinjamoor Akhil Srinivas, Hannah Dela Cruz, Ryan Mercer, Eamonn J. Keogh |
| 2023 | Matrix Profile XXX: MADRID: A Hyper-Anytime and Parameter-Free Algorithm to Find Time Series Anomalies of all Lengths. Yue Lu, Thirumalai Vinjamoor Akhil Srinivas, Takaaki Nakamura, Makoto Imamura, Eamonn J. Keogh |
| 2023 | Meteorology-Assisted Spatio-Temporal Graph Network for Uncivilized Urban Event Prediction. Yang Luo, Zehao Gu, Shiyang Zhou, Yun Xiong, Xiaofeng Gao |
| 2023 | Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation. Camilo Gomez, Pengyang Wang, Yanjie Fu |
| 2023 | Mitigating Multisource Biases in Graph Neural Networks via Real Counterfactual Samples. Zichong Wang, Giri Narasimhan, Xin Yao, Wenbin Zhang |
| 2023 | Mixtron: Bandit Online Multiclass Prediction with Implicit Feedback. Wanjin Feng, Hailong Shi, Peilin Zhao, Xingyu Gao |
| 2023 | Mixup-Inspired Video Class-Incremental Learning. Jinqiang Long, Yizhao Gao, Zhiwu Lu |
| 2023 | Model Cloaking against Gradient Leakage. Wenqi Wei, Ka-Ho Chow, Fatih Ilhan, Yanzhao Wu, Ling Liu |
| 2023 | Momentum is All You Need for Data-Driven Adaptive Optimization. Yizhou Wang, Yue Kang, Can Qin, Huan Wang, Yi Xu, Yulun Zhang, Yun Fu |
| 2023 | MoonKV: Optimizing Update-intensive Workloads for NVM-based Key-value Stores. Zhenghong Luo, Qian Wang, Haomai Wang, Tianshan Qu, Meng Li, Rong Gu, Haipeng Dai |
| 2023 | MtiRec: A Medical Test Recommender System based on the Analysis of Treatment Programs. Nengjun Zhu, Jieyun Huang, Jian Cao, Xinjiang Lu, Hao Liu, Hui Xiong |
| 2023 | Multi-Dictionary Tensor Decomposition. Maxwell McNeil, Petko Bogdanov |
| 2023 | Multi-Hop Correlation Preserving Hashing for Efficient Hamming Space Retrieval. Liang Li, Weiwei Sun |
| 2023 | Multi-Label Personalized Classification via Exclusive Sparse Tensor Factorization. Weijia Lin, Jiankun Wang, Lu Sun, Mineichi Kudo, Keigo Kimura |
| 2023 | Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences. Shuai Zhang, Chuan Zhou, Peng Zhang, Yang Liu, Zhao Li, Hongyang Chen |
| 2023 | Natural Language Generation Meets Data Visualization: Vis-to-Text and its Duality with Text-to-Vis. Yuanfeng Song, Xiaoling Huang, Xuefang Zhao, Raymond Chi-Wing Wong |
| 2023 | Neural Contextual Combinatorial Bandit under Non-stationary Environment. Jiaqi Zheng, Hedi Gao, Haipeng Dai, Zhenzhe Zheng, Fan Wu |
| 2023 | Non-Negative Matrix Factorization for Link Prediction Preserving Row and Column Spaces. Liping Yan, Weiren Yu |
| 2023 | On Computing Paradigms - Where Will Large Language Models Be Going. Xindong Wu, Xingquan Zhu, Elena Baralis, Ruqian Lu, Vipin Kumar, Leszek Rutkowski, Jie Tang |
| 2023 | On Regularized Sparse Logistic Regression. Mengyuan Zhang, Kai Liu |
| 2023 | On the Verification of Embeddings with Hybrid Markov Logic. Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal |
| 2023 | Online Ensemble of Ensemble OVA Framework for Class Evolution with Dominant Emerging Classes. Zhi Cao, Shuyi Zhang, Chin-Teng Lin |
| 2023 | PIX-GAN: Enhance Physics-Informed Estimation via Generative Adversarial Network. Haoran Li, Yang Weng |
| 2023 | PKAT: Pre-training in Collaborative Knowledge Graph Attention Network for Recommendation. Yi-Hong Lu, Chang-Dong Wang, Pei-Yuan Lai, Jian-Huang Lai |
| 2023 | PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection. Junjun Pan, Yixin Liu, Yizhen Zheng, Shirui Pan |
| 2023 | PatSTEG: Modeling Formation Dynamics of Patent Citation Networks via The Semantic-Topological Evolutionary Graph. Ran Miao, Xueyu Chen, Liang Hu, Zhifei Zhang, Minghua Wan, Qi Zhang, Cairong Zhao |
| 2023 | PatternRCA: A Pattern-Aware Root Cause Analysis Framework for Multi-Dimensional Time Series. Cheng He, Fulong Tian, Peijiao Xue, Yuan Wu, Yao Li, Jiajia Li, Zikai Wang, Feng Tan, Hongyang Chen, Linghe Kong |
| 2023 | Personalized Federated Semi-Supervised Learning with Black-Box Models. Siyin Huang, Shaoyuan Li, Songcan Chen |
| 2023 | Prediction in Long-term Evolution: Exploiting the Interaction Between Urban Crowd Flow Variation and POI Transition Patterns. Zhe Zheng, Jingjing Gu, Qiang Zhou, Xinjiang Lu |
| 2023 | Preference-Constrained Career Path Optimization: An Exploration Space-Aware Stochastic Model. Pengzhan Guo, Keli Xiao, Hengshu Zhu, Qingxin Meng |
| 2023 | Privacy-Preserving Cross-Domain Sequential Recommendation. Zhaohao Lin, Weike Pan, Zhong Ming |
| 2023 | Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches. Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng |
| 2023 | Pseudo-Labeling with Graph Active Learning for Few-shot Node Classification. Quan Li, Lingwei Chen, Shixiong Jing, Dinghao Wu |
| 2023 | RDKG: A Reinforcement Learning Framework for Disease Diagnosis on Knowledge Graph. Shipeng Guo, Kunpeng Liu, Pengfei Wang, Weiwei Dai, Yi Du, Yuanchun Zhou, Wenjuan Cui |
| 2023 | Refining the Unseen: Self-supervised Two-stream Feature Extraction for Image Quality Assessment. Yiwei Lou, Yanyuan Chen, Dexuan Xu, Doudou Zhou, Yongzhi Cao, Hanpin Wang, Yu Huang |
| 2023 | Reinforcement Learning based Hyper-heuristics for Many-objective Pickup and Delivery Problem. Adeem Ali Anwar, Xuyun Zhang |
| 2023 | Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection. Yuanchen Bei, Sheng Zhou, Qiaoyu Tan, Hao Xu, Hao Chen, Zhao Li, Jiajun Bu |
| 2023 | ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness. Yunfei Zhang, Chuan Qin, Dazhong Shen, Haiping Ma, Le Zhang, Xingyi Zhang, Hengshu Zhu |
| 2023 | Reserve Price optimization in First-Price Auctions via Multi-Task Learning. Achir Kalra, Chong Wang, Cristian Borcea, Yi Chen |
| 2023 | Resolving the Imbalance Issue in Hierarchical Disciplinary Topic Inference via LLM-based Data Augmentation. Xunxin Cai, Meng Xiao, Zhiyuan Ning, Yuanchun Zhou |
| 2023 | Rethinking Temporal Dependencies in Multiple Time Series: A Use Case in Financial Data. Patrick Asante Owusu, Etienne Gael Tajeuna, Jean-Marc Patenaude, Armelle Brun, Shengrui Wang |
| 2023 | Review-Incorporated Model-Agnostic Profile Injection Attacks on Recommender Systems. Shiyi Yang, Lina Yao, Chen Wang, Xiwei Xu, Liming Zhu |
| 2023 | Robust Network Alignment with the Combination of Structure and Attribute Embeddings. Jingkai Peng, Fei Xiong, Shirui Pan, Liang Wang, Xi Xiong |
| 2023 | Robust Semi-Supervised Learning for Self-learning Open-World Classes. Wenjuan Xi, Xin Song, Weili Guo, Yang Yang |
| 2023 | Robustness Certification of k-Nearest Neighbors. Nicolò Fassina, Francesco Ranzato, Marco Zanella |
| 2023 | Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization. Zexu Sun, Bowei He, Ming Ma, Jiakai Tang, Yuchen Wang, Chen Ma, Dugang Liu |
| 2023 | Rule Mining for Correcting Classification Models. Hirofumi Suzuki, Hiroaki Iwashita, Takuya Takagi, Yuta Fujishige, Satoshi Hara |
| 2023 | SCRIPT: Sequential Cross-Meta-Information Recommendation in Pretrain and Prompt Paradigm. Xinyi Zhou, Jipeng Jin, Li Ma, Xiaofeng Gao, Jianbo Yang, Xiongwen Yang, Lei Xiao |
| 2023 | SGD Biased towards Early Important Samples for Efficient Training. Alessio Quercia, Abigail Morrison, Hanno Scharr, Ira Assent |
| 2023 | SOAC: Supervised Off-Policy Actor-Critic for Recommender Systems. Shiqing Wu, Guandong Xu, Xianzhi Wang |
| 2023 | STSD: Modeling Spatial Temporal Staticity and Dynamicity in Traffic Forecasting. Guanghui Zhu, Haojun Hou, Peiliang Wang, Chunfeng Yuan, Yihua Huang |
| 2023 | Self-optimizing Feature Generation via Categorical Hashing Representation and Hierarchical Reinforcement Crossing. Wangyang Ying, Dongjie Wang, Kunpeng Liu, Leilei Sun, Yanjie Fu |
| 2023 | Self-supervised Heterogeneous Hypergraph Learning with Context-aware Pooling for Graph-level Classification. Malik Khizar Hayat, Shan Xue, Jian Yang |
| 2023 | Self-supervised Pre-training for Robust and Generic Spatial-Temporal Representations. Mingzhi Hu, Zhuoyun Zhong, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo |
| 2023 | Session-based Interactive Recommendation via Deep Reinforcement Learning. Longxiang Shi, Zilin Zhang, Shoujin Wang, Qi Zhang, Minghui Wu, Cheng Yang, Shijian Li |
| 2023 | SimEXT: Self-supervised Representation Learning for Extreme Values in Time Series. Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo |
| 2023 | Sparse Attacks for Manipulating Explanations in Deep Neural Network Models. Ahmad Ajalloeian, Seyed-Mohsen Moosavi-Dezfooli, Michalis Vlachos, Pascal Frossard |
| 2023 | Spatio-Temporal Hypergraph Neural ODE Network for Traffic Forecasting. Chengzhi Yao, Zhi Li, Junbo Wang |
| 2023 | Stochastic Integrated Explanations for Vision Models. Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein |
| 2023 | Take CARE: Improving Inherent Robustness of Spiking Neural Networks with Channel-wise Activation Recalibration Module. Yan Zhang, Cheng Chen, Dian Shen, Meng Wang, Beilun Wang |
| 2023 | Telecom Fraud Detection Based on Feature Binning and Autoencoder. Fei-Yao Liang, Fei-Peng Li, Ronghai Xu, Wei Cheng, Shi-Xian Deng, Zhe-Rui Yang, Chang-Dong Wang |
| 2023 | TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions. Taehyung Kwon, Jihoon Ko, Jinhong Jung, Kijung Shin |
| 2023 | Themis: Detecting Anomalies from Disguised Normal Financial Activities. Rui Ding, Xiaochun Yang, Bin Wang |
| 2023 | Theoretical Evaluation of Asymmetric Shapley Values for Root-Cause Analysis. Domokos M. Kelen, Mihály Petreczky, Péter Kersch, András A. Benczúr |
| 2023 | To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data. Hechuan Wen, Tong Chen, Li Kheng Chai, Shazia Sadiq, Kai Zheng, Hongzhi Yin |
| 2023 | Toward Interpretable Graph Neural Networks via Concept Matching Model. Tien-Cuong Bui, Wen-Syan Li |
| 2023 | Towards Unsupervised Graph Completion Learning on Graphs with Features and Structure Missing. Sichao Fu, Qinmu Peng, Yang He, Baokun Du, Xinge You |
| 2023 | Tree-based Kendall's τ Maximization for Explainable Unsupervised Anomaly Detection. Lanfang Kong, Alexis Huet, Dario Rossi, Mauro Sozio |
| 2023 | Two-Level Graph Representation Learning with Community-as-a-Node Graphs. Jeongha Park, Kisung Lee, Hyuk-Yoon Kwon |
| 2023 | Uncertainty-aware Traffic Prediction under Missing Data. Hao Mei, Junxian Li, Zhiming Liang, Guanjie Zheng, Bin Shi, Hua Wei |
| 2023 | Unfairness in Distributed Graph Frameworks. Hao Zhang, Malith Jayaweera, Bin Ren, Yanzhi Wang, Sucheta Soundarajan |
| 2023 | Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He |
| 2023 | Using UAV-Based Multispectral Imagery, Data-Driven Models, and Spatial Cross-Validation for Corn Grain Yield Prediction. Patrick Killeen, Iluju Kiringa, Tet Hin Yeap, Paula Branco |
| 2023 | Variable-length Encoding Framework: A Generic Framework for Enhancing the Accuracy of Approximate Membership Queries. Haipeng Dai, Hancheng Wang, Zhipeng Chen, Jiaqi Zheng, Meng Li, Rong Gu, Chen Tian, Wanchun Dou |
| 2023 | Variational Collective Graph AutoEncoder for Multi-behavior Recommendation. Yang Liu, Qianzhen Rao, Weike Pan, Zhong Ming |