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ORCID29th KDD 2023: Long Beach, CA, USA
- Ambuj K. Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar, Fatma Ozcan, Jieping Ye:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023. ACM 2023
Research Track Full Papers
- Florian Adriaens
, Honglian Wang, Aristides Gionis:
Minimizing Hitting Time between Disparate Groups with Shortcut Edges. 1-10 - Rishi Advani, Paolo Papotti, Abolfazl Asudeh:
Maximizing Neutrality in News Ordering. 11-24 - Amine Allouah, Christian Kroer, Xuan Zhang, Vashist Avadhanula, Nona Bohanon, Anil Dania, Caner Gocmen, Sergey Pupyrev, Parikshit Shah, Nicolás Stier Moses, Ken Rodríguez Taarup:
Fair Allocation Over Time, with Applications to Content Moderation. 25-35 - Mario Almagro, Emilio J. Almazán, Diego Ortego, David Jiménez:
LEA: Improving Sentence Similarity Robustness to Typos Using Lexical Attention Bias. 36-46 - Amel Awadelkarim, Arjun Seshadri, Itai Ashlagi, Irene Lo, Johan Ugander:
Rank-heterogeneous Preference Models for School Choice. 47-56 - Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song:
Knowledge Graph Reasoning over Entities and Numerical Values. 57-68 - Ergute Bao, Dawei Gao, Xiaokui Xiao, Yaliang Li:
Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting. 69-79 - Anna Beer, Andrew Draganov, Ellen Hohma, Philipp Jahn, Christian M. M. Frey, Ira Assent:
Connecting the Dots - Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering. 80-92 - Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi:
Sketch-Based Anomaly Detection in Streaming Graphs. 93-104 - Adam Breuer, Nazanin Khosravani Tehrani, Michael Tingley, Bradford Cottel:
Preemptive Detection of Fake Accounts on Social Networks via Multi-Class Preferential Attachment Classifiers. 105-116 - Fanchen Bu, Kijung Shin:
On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. 117-129 - Donghong Cai, Junru Chen, Yang Yang, Teng Liu, Yafeng Li:
MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals. 130-141 - Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei Chen, Yang Yang:
When to Pre-Train Graph Neural Networks? From Data Generation Perspective! 142-153 - Zeyu Cao, Zhipeng Liang, Bingzhe Wu, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao:
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. 154-166 - Chengliang Chai, Jiayi Wang, Nan Tang, Ye Yuan, Jiabin Liu, Yuhao Deng, Guoren Wang:
Efficient Coreset Selection with Cluster-based Methods. 167-178 - Deepayan Chakrabarti:
SURE: Robust, Explainable, and Fair Classification without Sensitive Attributes. 179-189 - Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister:
Data-Efficient and Interpretable Tabular Anomaly Detection. 190-201 - Jiadong Chen, Yang Luo, Xiuqi Huang, Fuxin Jiang, Yangguang Shi, Tieying Zhang, Xiaofeng Gao:
IPOC: An Adaptive Interval Prediction Model based on Online Chasing and Conformal Inference for Large-Scale Systems. 202-212 - Jiayi Chen, Aidong Zhang:
On Hierarchical Disentanglement of Interactive Behaviors for Multimodal Spatiotemporal Data with Incompleteness. 213-225 - Junfan Chen, Richong Zhang, Junchi Chen, Chunming Hu, Yongyi Mao:
Open-Set Semi-Supervised Text Classification with Latent Outlier Softening. 226-236 - Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song:
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization. 237-249 - Yixin Chen, Alan Kuhnle:
Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time. 250-261 - Zhen Chen, Xingzhi Guo, Baojian Zhou, Deqing Yang, Steven Skiena:
Accelerating Personalized PageRank Vector Computation. 262-273 - Zhijun Chen, Hailong Sun, Wanhao Zhang, Chunyi Xu, Qianren Mao, Pengpeng Chen:
Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler. 274-285 - Hung-Yun Chiang, Yi-Syuan Chen, Yun-Zhu Song, Hong-Han Shuai, Jason S. Chang:
Shilling Black-box Review-based Recommender Systems through Fake Review Generation. 286-297 - Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin:
Classification of Edge-dependent Labels of Nodes in Hypergraphs. 298-309 - Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang:
Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers. 310-322 - Corinna Coupette, Stefan Neumann, Aristides Gionis:
Reducing Exposure to Harmful Content via Graph Rewiring. 323-334 - Guanyu Cui, Zhewei Wei:
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem. 335-347 - Joscha Cüppers, Jilles Vreeken:
Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns. 348-357 - Kunal Dahiya, Sachin Yadav, Sushant Sondhi, Deepak Saini, Sonu Mehta, Jian Jiao, Sumeet Agarwal, Purushottam Kar, Manik Varma:
Deep Encoders with Auxiliary Parameters for Extreme Classification. 358-367 - Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang:
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. 368-379 - Shitong Dai, Jiongnan Liu, Zhicheng Dou, Haonan Wang, Lin Liu, Bo Long, Ji-Rong Wen:
Contrastive Learning for User Sequence Representation in Personalized Product Search. 380-389 - Pengtao Dang, Haiqi Zhu, Tingbo Guo, Changlin Wan, Tong Zhao, Paul Salama, Yijie Wang, Sha Cao, Chi Zhang:
Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation. 390-401 - Trisha Das, Zifeng Wang, Jimeng Sun:
TWIN: Personalized Clinical Trial Digital Twin Generation. 402-413 - Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, Shiliang Pu, Weihao Jiang:
Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds. 414-425 - Hongyuan Dong, Weinan Zhang, Wanxiang Che:
MetricPrompt: Prompting Model as a Relevance Metric for Few-shot Text Classification. 426-436 - Peiran Dong, Song Guo, Junxiao Wang:
Investigating Trojan Attacks on Pre-trained Language Model-powered Database Middleware. 437-447 - Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao:
Localised Adaptive Spatial-Temporal Graph Neural Network. 448-458 - Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam:
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. 459-469 - Gabriel Franco, Mark Crovella, Giovanni Comarela:
Dependence and Model Selection in LLP: The Problem of Variants. 470-481 - Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong:
Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling. 482-494 - Tingchen Fu, Xueliang Zhao, Rui Yan:
Delving into Global Dialogue Structures: Structure Planning Augmented Response Selection for Multi-turn Conversations. 495-505 - Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu:
Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design. 506-517 - Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan:
Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations. 518-530 - Haoyu Geng, Runzhong Wang, Fei Wu, Junchi Yan:
GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction. 531-543 - Matt Gorbett, Hossein Shirazi, Indrakshi Ray:
Sparse Binary Transformers for Multivariate Time Series Modeling. 544-556 - Jiaqi Gu, Guosheng Yin:
3D-Polishing for Triangular Mesh Compression of Point Cloud Data. 557-566 - Siyi Gu, Yifei Zhang, Yuyang Gao, Xiaofeng Yang, Liang Zhao:
ESSA: Explanation Iterative Supervision via Saliency-guided Data Augmentation. 567-576 - Hangzhi Guo, Thanh Hong Nguyen, Amulya Yadav:
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations. 577-589 - Jiarui Guo, Yisen Hong, Yuhan Wu, Yunfei Liu, Tong Yang, Bin Cui:
SketchPolymer: Estimate Per-item Tail Quantile Using One Sketch. 590-601 - Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang:
On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering. 602-613 - Yuhe Guo, Zhewei Wei:
Clenshaw Graph Neural Networks. 614-625 - Yuxiang Guo, Lu Chen, Zhengjie Zhou, Baihua Zheng, Ziquan Fang, Zhikun Zhang, Yuren Mao, Yunjun Gao:
CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution. 626-637 - Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du:
A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability. 638-648 - Mridul Gupta, Hariprasad Kodamana, Sayan Ranu:
Frigate: Frugal Spatio-temporal Forecasting on Road Networks. 649-660 - Kevin Han, Shuangning Li, Jialiang Mao, Han Wu:
Detecting Interference in Online Controlled Experiments with Increasing Allocation. 661-672 - Xiao Han, Xiangyu Zhao, Liang Zhang, Wanyu Wang:
Mitigating Action Hysteresis in Traffic Signal Control with Traffic Predictive Reinforcement Learning. 673-684 - Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li:
GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning. 685-697 - Jianfeng He, Xuchao Zhang, Shuo Lei, Abdulaziz Alhamadani, Fanglan Chen, Bei Xiao, Chang-Tien Lu:
CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning. 698-710 - Long He, Ho-Yin Mak:
Prescriptive PCA: Dimensionality Reduction for Two-stage Stochastic Optimization. 711-721 - Shuo He, Lei Feng, Guowu Yang:
Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples. 722-731 - Christine Herlihy, Aviva Prins, Aravind Srinivasan, John P. Dickerson:
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting. 732-740 - Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya:
Unbiased Locally Private Estimator for Polynomials of Laplacian Variables. 741-751 - Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann:
Graph Neural Processes for Spatio-Temporal Extrapolation. 752-763 - Mingzhi Hu, Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo:
ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSM. 764-774 - Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, Shangsong Liang:
Leveraging Relational Graph Neural Network for Transductive Model Ensemble. 775-787 - Shaoyuan Huang, Zheng Wang, Heng Zhang, Xiaofei Wang, Cheng Zhang, Wenyu Wang:
One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms. 788-797 - Zijie Huang, Yizhou Sun, Wei Wang:
Generalizing Graph ODE for Learning Complex System Dynamics across Environments. 798-809 - Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles. 810-821 - Alexandra Iacob, Bogdan Cautis, Silviu Maniu:
Sequential Learning Algorithms for Contextual Model-Free Influence Maximization. 822-831 - Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder:
COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. 832-844 - Tsuyoshi Idé, Naoki Abe:
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution. 845-856 - Makoto Imamura, Takaaki Nakamura:
Parameter-free Spikelet: Discovering Different Length and Warped Time Series Motifs using an Adaptive Time Series Representation. 857-866 - Yeonjun In, Kanghoon Yoon, Chanyoung Park:
Similarity Preserving Adversarial Graph Contrastive Learning. 867-878 - Jun-Gi Jang, Jeongyoung Lee, Yong-chan Park, U Kang:
Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors - Algorithm and Application. 879-890 - Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting. 891-900 - Sheo Yon Jhin, Jaehoon Lee, Noseong Park:
Precursor-of-Anomaly Detection for Irregular Time Series. 917-929 - Shuo Ji, Xiaodong Lu, Mingzhe Liu, Leilei Sun, Chuanren Liu, Bowen Du, Hui Xiong:
Community-based Dynamic Graph Learning for Popularity Prediction. 930-940 - Ran Jia, Haoming Guo, Xiaoyuan Jin, Chao Yan, Lun Du, Xiaojun Ma, Tamara Stankovic, Marko Lozajic, Goran Zoranovic, Igor Ilic, Shi Han, Dongmei Zhang:
GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network. 941-950 - Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin:
Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks. 951-963 - Yuheng Jia, Jiahao Jiang, Yongheng Wang:
Semantic Dissimilarity Guided Locality Preserving Projections for Partial Label Dimensionality Reduction. 964-973 - Yuheng Jia, Chongjie Si, Min-Ling Zhang:
Complementary Classifier Induced Partial Label Learning. 974-983 - Minqi Jiang, Songqiao Han, Hailiang Huang:
Anomaly Detection with Score Distribution Discrimination. 984-996 - Song Jiang, Zijie Huang, Xiao Luo, Yizhou Sun:
CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems. 997-1009 - Yushan Jiang, Wenchao Yu, Dongjin Song, Lu Wang, Wei Cheng, Haifeng Chen:
FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation. 1010-1019 - Bowen Jin, Yu Zhang, Qi Zhu, Jiawei Han:
Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks. 1020-1031 - Yilun Jin, Kai Chen, Qiang Yang:
Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across Cities. 1032-1043 - Yiqiao Jin, Yeon-Chang Lee, Kartik Sharma, Meng Ye, Karan Sikka, Ajay Divakaran, Srijan Kumar:
Predicting Information Pathways Across Online Communities. 1044-1056 - Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. 1057-1072 - Xuan Kan, Zimu Li, Hejie Cui, Yue Yu, Ran Xu, Shaojun Yu, Zilong Zhang, Ying Guo, Carl Yang:
R-Mixup: Riemannian Mixup for Biological Networks. 1073-1085 - Gayeong Kim, Sookyung Kim, Ko Keun Kim, Suchan Park, Heesoo Jung, Hogun Park:
Exploiting Relation-aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning. 1086-1096 - Sang-Hong Kim, Ha-Myung Park:
Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest. 1097-1106 - Sein Kim, Namkyeong Lee, Donghyun Kim, Min-Chul Yang, Chanyoung Park:
Task Relation-aware Continual User Representation Learning. 1107-1119 - Sungwon Kim, Junseok Lee, Namkyeong Lee, Wonjoong Kim, Seungyoon Choi, Chanyoung Park:
Task-Equivariant Graph Few-shot Learning. 1120-1131 - Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin:
How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. 1132-1143 - Taeho Kim, Juwon Yu, Won-Yong Shin, Hyunyoung Lee, Ji-Hui Im, Sang-Wook Kim:
LATTE: A Framework for Learning Item-Features to Make a Domain-Expert for Effective Conversational Recommendation. 1144-1153 - Haruka Kiyohara, Masatoshi Uehara, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto, Yuta Saito:
Off-Policy Evaluation of Ranking Policies under Diverse User Behavior. 1154-1163 - Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung:
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning. 1164-1175 - Mayuresh Kunjir, Sanjay Chawla, Siddarth Chandrasekar, Devika Jay, Balaraman Ravindran:
Optimizing Traffic Control with Model-Based Learning: A Pessimistic Approach to Data-Efficient Policy Inference. 1176-1187 - Tian Lan, Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, Chen Zhang:
MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis. 1188-1199 - Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park:
Shift-Robust Molecular Relational Learning with Causal Substructure. 1200-1212 - Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang:
Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. 1213-1222 - Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan:
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. 1223-1234 - Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui:
Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. 1235-1247 - Jiacheng Li, Zhankui He, Jingbo Shang, Julian J. McAuley:
UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation. 1248-1257 - Jiacheng Li, Ming Wang, Jin Li, Jinmiao Fu, Xin Shen, Jingbo Shang, Julian J. McAuley:
Text Is All You Need: Learning Language Representations for Sequential Recommendation. 1258-1267