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ORCID21st ICDM 2021: Auckland, New Zealand
- James Bailey, Pauli Miettinen, Yun Sing Koh, Dacheng Tao, Xindong Wu:
IEEE International Conference on Data Mining, ICDM 2021, Auckland, New Zealand, December 7-10, 2021. IEEE 2021, ISBN 978-1-6654-2398-4 - Francesco Alesiani
, Shujian Yu, Xi Yu:
Gated Information Bottleneck for Generalization in Sequential Environments. 1-10 - Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Taylor T. Johnson:
Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature. 11-20 - Lodewijk Brand, Lauren Zoe Baker, Carla Ellefsen, Jackson Sargent, Hua Wang:
A Linear Primal-Dual Multi-Instance SVM for Big Data Classifications. 21-30 - Wennan Chang, Pengdao Dang, Changlin Wan, Xiaoyu Lu, Yue Fang, Tong Zhao, Yong Zang, Bo Li, Chi Zhang, Sha Cao:
Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence. 31-40 - Huiping Chen, Changyu Dong, Liyue Fan, Grigorios Loukides, Solon P. Pissis, Leen Stougie:
Differentially Private String Sanitization for Frequency-Based Mining Tasks. 41-50 - Mingyue Cheng, Fajie Yuan, Qi Liu, Xin Xin, Enhong Chen:
Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-training. 51-60 - Eli Chien, Chao Pan, Puoya Tabaghi, Olgica Milenkovic:
Highly Scalable and Provably Accurate Classification in Poincaré Balls. 61-70 - Rob Churchill, Lisa Singh:
Topic-Noise Models: Modeling Topic and Noise Distributions in Social Media Post Collections. 71-80 - Noy Cohen-Shapira, Lior Rokach:
TRIO: Task-agnostic dataset representation optimized for automatic algorithm selection. 81-90 - Cazamere Comrie, Jon M. Kleinberg:
Hypergraph Ego-networks and Their Temporal Evolution. 91-100 - Manqing Dong, Lina Yao, Xianzhi Wang, Xiwei Xu, Liming Zhu:
MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta Learning. 101-110 - Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu:
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network. 111-120 - Yangcheng Gao, Zhao Zhang, Haijun Zhang, Mingbo Zhao, Yi Yang, Meng Wang:
Dictionary Pair-based Data-Free Fast Deep Neural Network Compression. 121-130 - Yuyang Gao, Tong Steven Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Ray Hong, Liang Zhao:
GNES: Learning to Explain Graph Neural Networks. 131-140 - Andrey Gritsenko, Yuan Guo, Kimia Shayestehfard, Armin Moharrer, Jennifer G. Dy, Stratis Ioannidis:
Graph Transfer Learning. 141-150 - Bin Gu, Zhou Zhai, Xiang Li, Heng Huang:
Finding Age Path of Self-Paced Learning. 151-160 - Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. 161-170 - Ido Hakimi, Rotem Zamir Aviv, Kfir Y. Levy, Assaf Schuster:
LAGA: Lagged AllReduce with Gradient Accumulation for Minimal Idle Time. 171-180 - Yishuo Zhang, Nayyar Abbas Zaidi, Jiahui Zhou, Gang Li:
GANBLR: A Tabular Data Generation Model. 181-190 - Yi He, Jiaxian Dong, Bo-Jian Hou, Yu Wang, Fei Wang:
Online Learning in Variable Feature Spaces with Mixed Data. 181-190 - Yilin Hou, Guangming Zhao, Chuanren Liu, Zhonglin Zu, Xiaoqiang Zhu:
Conversion Prediction with Delayed Feedback: A Multi-task Learning Approach. 191-199 - Chen Huang, Liangxu Pan, Qinli Yang, Hongliang Wang, Junming Shao:
Flexible, Robust, Scalable Semi-supervised Learning via Reliability Propagation. 200-209 - Jie Huang, Qi Liu, Fei Wang, Zhenya Huang, Songtao Fang, Runze Wu, Enhong Chen, Yu Su, Shijin Wang:
Group-Level Cognitive Diagnosis: A Multi-Task Learning Perspective. 210-219 - Ye Huang, Wei Huang, Shiwei Tong, Zhenya Huang, Qi Liu, Enhong Chen, Jianhui Ma, Liang Wan, Shijin Wang:
STAN: Adversarial Network for Cross-domain Question Difficulty Prediction. 220-229 - Jeehyun Hwang, Jeongwhan Choi, Hwangyong Choi, Kookjin Lee, Dongeun Lee, Noseong Park:
Climate Modeling with Neural Diffusion Equations. 230-239 - Hankyu Jang, Shreyas Pai, Bijaya Adhikari, Sriram V. Pemmaraju:
Risk-aware Temporal Cascade Reconstruction to Detect Asymptomatic Cases : For the CDC MInD Healthcare Network. 240-249 - Sheo Yon Jhin, Heejoo Shin, Seoyoung Hong, Minju Jo, Solhee Park, Noseong Park, Seungbeom Lee, Hwiyoung Maeng, Seungmin Jeon:
Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting. 250-259 - Renqi Jia, Xiaofei Zhou, Linhua Dong, Shirui Pan:
Hypergraph Convolutional Network for Group Recommendation. 260-269 - Xiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Jordan S. Read:
Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems. 270-279 - Xiangping Kang, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Wei Guo, Yazhou Ren, Lizhen Cui:
Crowdsourcing with Self-paced Workers. 280-289 - Yun-Yong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, Sang-Wook Kim:
MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems. 290-299 - Yuandu Lai, Yahong Han, Yaowei Wang:
Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings. 300-309 - Geon Lee, Kijung Shin:
THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting. 310-319 - Xiaoyu Li, Chen Li, Yuhua Wei, Yuyao Sun, Jishang Wei, Xiang Li, Buyue Qian:
BaT: Beat-aligned Transformer for Electrocardiogram Classification. 320-329 - Xujia Li, Yanyan Shen, Lei Chen:
Mcore: Multi-Agent Collaborative Learning for Knowledge-Graph-Enhanced Recommendation. 330-339 - Yang Li, Xianli Zhang, Buyue Qian, Zeyu Gao, Chong Guan, Yefeng Zheng, Hansen Zheng, Fenglang Wu, Chen Li:
Towards Interpretability and Personalization: A Predictive Framework for Clinical Time-series Analysis. 340-349 - Yunchuan Li, Yan Zhao, Kai Zheng:
Preference-aware Group Task Assignment in Spatial Crowdsourcing: A Mutual Information-based Approach. 350-359 - Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, Bin Wang:
Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences. 360-369 - Yang Lin, Irena Koprinska, Mashud Rana:
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting. 370-378 - Chen Ling, Carl Yang, Liang Zhao:
Deep Generation of Heterogeneous Networks. 379-388 - Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Chunli Liu, Qi Liu, Enhong Chen:
Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural Network. 389-398 - Kunpeng Liu, Pengfei Wang, Dongjie Wang, Wan Du, Dapeng Oliver Wu, Yanjie Fu:
Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy. 399-408 - Yifei Liu, Chao Chen, Yazheng Liu, Xi Zhang, Sihong Xie:
Multi-objective Explanations of GNN Predictions. 409-418 - Tomas Martin, Petko Valtchev, Louis-Romain Roux:
FGC-Stream: A novel joint miner for frequent generators and closed itemsets in data streams. 419-428 - Md. Parvez Mollah, Vinícius M. A. de Souza, Abdullah Mueen:
Multi-way Time Series Join on Multi-length Patterns. 429-438 - Mehrnaz Najafi, Lifang He, Philip S. Yu:
Outlier-Robust Multi-View Subspace Clustering with Prior Constraints. 439-448 - Shuai Niu, Qing Yin, Yunya Song, Yike Guo, Xian Yang:
Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records. 449-458 - Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein:
Cutting to the Chase with Warm-Start Contextual Bandits. 459-468 - Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, Dongsheng Li:
Towards Generating Real-World Time Series Data. 469-478 - Jingshu Peng, Yanyan Shen, Lei Chen:
GraphANGEL: Adaptive aNd Structure-Aware Sampling on Graph NEuraL Networks. 479-488 - Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Sequential Diagnosis Prediction with Transformer and Ontological Representation. 489-498 - Thai-Hoang Pham, Changchang Yin, Laxmi Mehta, Xueru Zhang, Ping Zhang:
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning. 499-508 - Gaël Poux-Médard, Julien Velcin, Sabine Loudcher:
Powered Hawkes-Dirichlet Process: Challenging Textual Clustering using a Flexible Temporal Prior. 509-518 - Ruihong Qiu, Zi Huang, Hongzhi Yin:
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation. 519-528 - Jiahuan Ren, Zhao Zhang, Jicong Fan, Haijun Zhang, Mingliang Xu, Meng Wang:
Robust Low-rank Deep Feature Recovery in CNNs: Toward Low Information Loss and Fast Convergence. 529-538 - Nasim Sabetpour, Adithya Kulkarni, Sihong Xie, Qi Li:
Truth Discovery in Sequence Labels from Crowds. 539-548 - Dhruv Sahnan, Snehil Dahiya, Vasu Goel, Anil Bandhakavi, Tanmoy Chakraborty:
Better Prevent than React: Deep Stratified Learning to Predict Hate Intensity of Twitter Reply Chains. 549-558 - Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu:
Fast Attributed Graph Embedding via Density of States. 559-568 - Dev Yashpal Sheth, Arun Rajkumar:
PARWiS: Winner determination from Active Pairwise Comparisons under a Shoestring Budget. 569-578 - Tongtong Su, Qiyu Liang, Jinsong Zhang, Zhaoyang Yu, Gang Wang, Xiaoguang Liu:
Attention-based Feature Interaction for Efficient Online Knowledge Distillation. 579-588 - Chang Wei Tan, Matthieu Herrmann, Geoffrey I. Webb:
Ultra fast warping window optimization for Dynamic Time Warping. 589-598 - Qiao Tang, Hong Xie:
A Robust Algorithm to Unifying Offline Causal Inference and Online Multi-armed Bandit Learning. 599-608 - Nikolaj Tatti:
Fast computation of distance-generalized cores using sampling. 609-618 - Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Hang Zhang:
Isolation Kernel Density Estimation. 619-628 - Joshua Tobin, Mimi Zhang:
DCF: An Efficient and Robust Density-Based Clustering Method. 629-638 - Andrea Tonon, Fabio Vandin:
CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown Network. 639-648 - Amin Vahedian, Xun Zhou:
Precise Bayes Classifier: Summary of Results. 649-658 - Arthur Vervaet, Raja Chiky, Mar Callau-Zori:
USTEP: Unfixed Search Tree for Efficient Log Parsing. 659-668 - Dingrong Wang, Hitesh Sapkota, Xumin Liu, Qi Yu:
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval. 669-678 - Dongjie Wang, Kunpeng Liu, Pauline Johnson, Leilei Sun, Bowen Du, Yanjie Fu:
Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning. 679-688 - Lu Wang, Yan Li, Mark H. Chignell:
Combining Ranking and Point-wise Losses for Training Deep Survival Analysis Models. 689-698 - Xuesong Wang, Lina Yao, Xianzhi Wang, Hye-Young Paik, Sen Wang:
Global Convolutional Neural Processes. 699-708 - Wenjuan Wei, Lu Feng:
Nonlinear Causal Structure Learning for Mixed Data. 709-718 - Yuhua Wei, Xiaoyu Li, Jishang Wei, Buyue Qian, Chen Li:
Learning to Reweight Samples with Offline Loss Sequence. 719-728 - Jing Wen, Bi-Yi Chen, Chang-Dong Wang, Zhihong Tian:
PRGAN: Personalized Recommendation with Conditional Generative Adversarial Networks. 729-738 - Asiri Wijesinghe, Qing Wang, Stephen Gould:
A Regularized Wasserstein Framework for Graph Kernels. 739-748 - Di Wu, Cheng Chen, Xiujun Chen, Junwei Pan, Xun Yang, Qing Tan, Jian Xu, Kuang-Chih Lee:
Impression Allocation and Policy Search in Display Advertising. 749-756 - Meng Xiao, Ziyue Qiao, Yanjie Fu, Yi Du, Pengyang Wang, Yuanchun Zhou:
Expert Knowledge-Guided Length-Variant Hierarchical Label Generation for Proposal Classification. 757-766 - Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam:
A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity. 767-776 - Xiao Xu, Xian Xu, Yuyao Sun, Xiaoshuang Liu, Xiang Li, Guotong Xie, Fei Wang:
Predictive Modeling of Clinical Events with Mutual Enhancement Between Longitudinal Patient Records and Medical Knowledge Graph. 777-786 - Haoran Yang, Hongxu Chen, Lin Li, Philip S. Yu, Guandong Xu:
Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation. 787-796 - Peng Yang, Xiaoyun Li, Ping Li:
Graph-based Adversarial Online Kernel Learning with Adaptive Embedding. 797-806 - Shuo Yang, Zeyu Feng, Pei Du, Bo Du, Chang Xu:
Structure-Aware Stabilization of Adversarial Robustness with Massive Contrastive Adversaries. 807-816 - Song Yang, Jiamou Liu, Kaiqi Zhao:
Space Meets Time: Local Spacetime Neural Network For Traffic Flow Forecasting. 817-826 - Jaemin Yoo, Junghun Kim, Hoyoung Yoon, Geonsoo Kim, Changwon Jang, U Kang:
Accurate Graph-Based PU Learning without Class Prior. 827-836 - Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, Jiawei Han:
AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks. 837-846 - Jingyi Yuan, Yang Weng:
Physics Interpretable Shallow-Deep Neural Networks for Physical System Identification with Unobservability. 847-856 - Chengxi Zang, Fei Wang:
SCEHR: Supervised Contrastive Learning for Clinical Risk Prediction using Electronic Health Records. 857-866 - Ge Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, Quan Z. Sheng:
FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance. 867-876 - Jiuling Zhang, Zhiming Ding:
Robustifying DARTS by Eliminating Information Bypass Leakage via Explicit Sparse Regularization. 877-885 - Wenbin Zhang, Jeremy C. Weiss:
Fair Decision-making Under Uncertainty. 886-895 - Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, Xiwang Yang:
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations. 896-905 - Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, Jun Luo:
DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. 906-915 - Yunfeng Zhao, Guoxian Yu, Lei Liu, Zhongmin Yan, Carlotta Domeniconi, Lizhen Cui:
Few-Shot Partial Multi-Label Learning. 926-935 - Zhao Zhang, Weiming Jiang, Yang Wang, Qiaolin Ye, Mingbo Zhao, Mingliang Xu, Meng Wang:
Discriminative Additive Scale Loss for Deep Imbalanced Classification and Embedding. 936-945 - Zhao Zhang, Xianzhen Li, Haijun Zhang, Yi Yang, Shuicheng Yan, Meng Wang:
Triplet Deep Subspace Clustering via Self-Supervised Data Augmentation. 946-955 - Zicong Zhang, Changchang Yin, Ping Zhang:
Temporal Clustering with External Memory Network for Disease Progression Modeling. 956-965 - Ziming Zhang, Guojun Wu, Yanhua Li, Yun Yue, Xun Zhou:
Deep Incremental RNN for Learning Sequential Data: A Lyapunov Stable Dynamical System. 966-975 - Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim:
PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series. 976-981 - Muhammad Afif Ali, Suriya Venkatesan, Victor C. Liang, Hannes Kruppa:
TEST-GCN: Topologically Enhanced Spatial-Temporal Graph Convolutional Networks for Traffic Forecasting. 982-987 - Jonathan Amazon, Khurram Shafique, Zeeshan Rasheed, Aaron Reite:
DIVINIA: Rare Object Localization and Search in Overhead Imagery. 988-993 - Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Jonathan Weill, Noam Koenigstein:
Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates. 994-999 - Fabian Berns, Jan David Hüwel, Christian Beecks:
LOGIC: Probabilistic Machine Learning for Time Series Classification. 1000-1005 - Arkaitz Bidaurrazaga, Aritz Pérez, Marco Capó:
K-means for Evolving Data Streams. 1006-1011 - Zerui Cai:
Generating Explanations for Recommendation Systems via Injective VAE. 1012-1017 - Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie:
Self-learn to Explain Siamese Networks Robustly. 1018-1023 - Shengyu Chen, Alison P. Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan S. Read, Jeffrey M. Sadler, Jacob Zwart, Xiaowei Jia:
Heterogeneous Stream-reservoir Graph Networks with Data Assimilation. 1024-1029 - Yi-He Chen, Shen-Huan Lyu, Yuan Jiang:
Improving Deep Forest by Exploiting High-order Interactions. 1030-1035 - André Ferreira Cruz, Pedro Saleiro, Catarina Belém, Carlos Soares, Pedro Bizarro:
Promoting Fairness through Hyperparameter Optimization. 1036-1041 - Shaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, Junyu Dong:
Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference. 1042-1047 - Benjamin Denham, Edmund M.-K. Lai, Roopak Sinha, M. Asif Naeem:
Gain-Some-Lose-Some: Reliable Quantification Under General Dataset Shift. 1048-1053 - Wei Fan, Kunpeng Liu, Rui Xie, Hao Liu, Hui Xiong, Yanjie Fu:
Fair Graph Auto-Encoder for Unbiased Graph Representations with Wasserstein Distance. 1054-1059 - Yucai Fan, Yuhang Yao, Carlee Joe-Wong:
GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs. 1060-1065 - Yang Gao, Peng Zhang, Zhao Li, Chuan Zhou, Yongchao Liu, Yue Hu:
Heterogeneous Graph Neural Architecture Search. 1066-1071 - Michal Tomasz Godziszewski, Tomasz P. Michalak, Marcin Waniek, Talal Rahwan, Kai Zhou, Yulin Zhu:
Attacking Similarity-Based Sign Prediction. 1072-1077 - Hui Guan, Umana Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, Xipeng Shen:
Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. 1078-1083 - Guillaume Guarino, Ahmed Samet, Amir Nafi, Denis Cavallucci:
PaGAN: Generative Adversarial Network for Patent understanding. 1084-1089 - Anne Hartebrodt, Reza Nasirigerdeh, David B. Blumenthal, Richard Röttger:
Federated Principal Component Analysis for Genome-Wide Association Studies. 1090-1095 - Yuting He, Rongjun Ge, Jiasong Wu, Jean-Louis Coatrieux, Huazhong Shu, Yang Chen, Guanyu Yang, Shuo Li:
Thin Semantics Enhancement via High-Frequency Priori Rule for Thin Structures Segmentation. 1096-1101 - Hongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, Xuyun Zhang:
Source Inference Attacks in Federated Learning. 1102-1107 - Ningbo Huang, Gang Zhou, Mengli Zhang, Meng Zhang:
MC-RGCN: A Multi-Channel Recurrent Graph Convolutional Network to Learn High-Order Social Relations for Diffusion Prediction. 1108-1113 - Bo Hui, Da Yan, Haiquan Chen, Wei-Shinn Ku:
Trajectory WaveNet: A Trajectory-Based Model for Traffic Forecasting. 1114-1119 - Makoto Imamura, Takaaki Nakamura:
Spikelet: An Adaptive Symbolic Approximation for Finding Higher-Level Structure in Time Series. 1120-1125 - Roshni G. Iyer, Wei Wang, Yizhou Sun:
Bi-Level Attention Graph Neural Networks. 1126-1131 - Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding:
SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. 1132-1137 - Houye Ji, Cheng Yang, Chuan Shi, Pan Li:
Heterogeneous Graph Neural Network with Distance Encoding. 1138-1143 - Pengfei Jiao, Ruili Lu, Di Jin, Yinghui Wang, Huaming Wu:
An Effective and Robust Framework by Modeling Correlations of Multiplex Network Embedding. 1144-1149 - Yoonsuk Kang, Woncheol Lee, Yeon-Chang Lee, Kyungsik Han, Sang-Wook Kim:
Adversarial Learning of Balanced Triangles for Accurate Community Detection on Signed Networks. 1150-1155 - Wenwei Ke, Chuanren Liu, Xiangfu Shi, Yiqiao Dai, Philip S. Yu, Xiaoqiang Zhu:
Addressing Exposure Bias in Uplift Modeling for Large-scale Online Advertising. 1156-1161 - Wonjun Ko, Wonsik Jung, Eunjin Jeon, Ahmad Wisnu Mulyadi, Heung-Il Suk:
ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding. 1162-1167 - Jan Kocon, Marcin Gruza, Julita Bielaniewicz, Damian Grimling, Kamil Kanclerz, Piotr Milkowski, Przemyslaw Kazienko:
Learning Personal Human Biases and Representations for Subjective Tasks in Natural Language Processing. 1168-1173 - Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum:
Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning. 1174-1179 - Dongha Lee, Su Kim, Seonghyeon Lee, Chanyoung Park, Hwanjo Yu:
Learnable Structural Semantic Readout for Graph Classification. 1180-1185 - Dongha Lee, Dongmin Hyun, Jiawei Han, Hwanjo Yu:
Out-of-Category Document Identification Using Target-Category Names as Weak Supervision. 1186-1191 - Ween Jiann Lee, Maksim Tkachenko, Hady W. Lauw:
Robust BiPoly-Matching for Multi-Granular Entities. 1192-1197 - Wen-Zhi Li, Ling Huang, Chang-Dong Wang, Yuxin Ye:
StarGAT: Star-Shaped Hierarchical Graph Attentional Network for Heterogeneous Network Representation Learning. 1198-1203 - Angelica Liguori, Giuseppe Manco, Francesco Sergio Pisani, Ettore Ritacco:
Adversarial Regularized Reconstruction for Anomaly Detection and Generation. 1204-1209 - M. Vijaikumar, Deepesh V. Hada, Shirish K. Shevade:
HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List Continuation. 1210-1215 - Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Sivasubramanium Bhavani, Joyce C. Ho:
Communication Efficient Tensor Factorization for Decentralized Healthcare Networks. 1216-1221 - Marcelo Rodrigues de Holanda Maia, Alexandre Plastino, Alex Alves Freitas:
An Ensemble of Naive Bayes Classifiers for Uncertain Categorical Data. 1222-1227 - André Gustavo Maletzke, Denis Moreira dos Reis, Waqar Hassan, Gustavo Batista:
Accurately Quantifying under Score Variability. 1228-1233 - João Pedro Rodrigues Mattos, Ricardo M. Marcacini:
Semi-Supervised Graph Attention Networks for Event Representation Learning. 1234-1239 - Ryan Mercer, Sara Alaee, Alireza Abdoli, Shailendra Singh, Amy C. Murillo, Eamonn J. Keogh:
Matrix Profile XXIII: Contrast Profile: A Novel Time Series Primitive that Allows Real World Classification. 1240-1245 - Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. 1246-1251 - Mohammad Hossein Nazeri, Mahdi Bohlouli:
Exploring Reflective Limitation of Behavior Cloning in Autonomous Vehicles. 1252-1257 - Krishna Prasad Neupane, Ervine Zheng, Qi Yu:
MetaEDL: Meta Evidential Learning For Uncertainty-Aware Cold-Start Recommendations. 1258-1263 - Eunkyu Oh, Taehun Kim, Yunhu Ji, Sushil Khyalia:
STING: Self-attention based Time-series Imputation Networks using GAN. 1264-1269 - Qiao Pan, Ke Ding, Dehua Chen:
Multi-Classification Prediction of Alzheimer's Disease based on Fusing Multi-modal Features. 1270-1275 - Jiaqi Peng, Jinxia Guo, Qinli Yang, Jianyun Lu, Junming Shao:
A general framework for mining concept-drifting data streams with evolvable features. 1276-1281 - Li Qian, Claudia Plant, Christian Böhm:
Density-Based Clustering for Adaptive Density Variation. 1282-1287 - Yijian Qin, Xin Wang, Peng Cui, Wenwu Zhu:
GQNAS: Graph Q Network for Neural Architecture Search. 1288-1293 - Chuanwei Qu, Kuangmeng Wang, Hong Zhang, Guoxian Yu, Carlotta Domeniconi:
Incomplete Multi-view Multi-label Active Learning. 1294-1299 - Shaogang Ren, Haiyan Yin, Mingming Sun, Ping Li:
Causal Discovery with Flow-based Conditional Density Estimation. 1300-1305 - Michael Ruchte, Josif Grabocka:
Scalable Pareto Front Approximation for Deep Multi-Objective Learning. 1306-1311 - Yoichi Sasaki, Yuzuru Okajima:
Alternative Ruleset Discovery to Support Black-box Model Predictions. 1312-1317 - Yasas Senarath, Ayan Mukhopadhyay, Sayyed Mohsen Vazirizade, Hemant Purohit, Saideep Nannapaneni, Abhishek Dubey:
Practitioner-Centric Approach for Early Incident Detection Using Crowdsourced Data for Emergency Services. 1318-1323 - Mandar Sharma, John S. Brownstein, Naren Ramakrishnan:
T3: Domain-Agnostic Neural Time-series Narration. 1324-1329 - Blaz Skrlj, Matej Petkovic:
Compressibility of Distributed Document Representations. 1330-1335 - Yuanfeng Song, Xiaoling Huang, Xuefang Zhao, Di Jiang, Raymond Chi-Wing Wong:
Multimodal N-best List Rescoring with Weakly Supervised Pre-training in Hybrid Speech Recognition. 1336-1341 - Wu-Jiu Sun, Xiao Fan Liu, Fei Shen:
Learning Dynamic User Interactions for Online Forum Commenting Prediction. 1342-1347 - Zhe Tang, Zhengyun Chen, Fang Qi, Lingyan Zhang, Shuhong Chen:
Pest-YOLO: Deep Image Mining and Multi-Feature Fusion for Real-Time Agriculture Pest Detection. 1348-1353 - Meet Taraviya, Anurag Beniwal, Yen-Liang Lin, Larry Davis:
PSANet - subspace attention for personalized compatibility. 1354-1360 - Sheng Tian, Tao Xiong, Leilei Shi:
Streaming Dynamic Graph Neural Networks for Continuous-Time Temporal Graph Modeling. 1361-1366 - Tarik Reza Toha, Masfiqur Rahaman, Saiful Islam Salim, Mainul Hossain, Arif Mohaimin Sadri, A. B. M. Alim Al Islam:
DhakaNet: Unstructured Vehicle Detection using Limited Computational Resources. 1367-1372 - Panagiotis A. Traganitis, Georgios B. Giannakis:
Detecting adversaries in Crowdsourcing. 1373-1378 - Guihong Wan, Haim Schweitzer:
A Lookahead Algorithm for Robust Subspace Recovery. 1379-1384 - Daheng Wang, Tong Zhao, Nitesh V. Chawla, Meng Jiang:
Dynamic Attributed Graph Prediction with Conditional Normalizing Flows. 1385-1390 - Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, Wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, Yun Fu:
Aspect-based Sentiment Classification via Reinforcement Learning. 1391-1396 - Wei-Yao Wang, Teng-Fong Chan, Hui-Kuo Yang, Chih-Chuan Wang, Yao-Chung Fan, Wen-Chih Peng:
Exploring the Long Short-Term Dependencies to Infer Shot Influence in Badminton Matches. 1397-1402 - Yuwei Wang, Yan Zheng, Yanqing Peng, Chin-Chia Michael Yeh, Zhongfang Zhuang, Mahashweta Das, Mangesh Bendre, Feifei Li, Wei Zhang, Jeff M. Phillips:
Constrained Non-Affine Alignment of Embeddings. 1403-1408 - Yongjie Wang, Ke Wang, Cheng Long, Chunyan Miao:
Summarizing User-Item Matrix By Group Utility Maximization. 1409-1414 - Xiaosu Wang, Yun Xiong, Hao Niu, Jingwen Yue, Yangyong Zhu, Philip S. Yu:
BioHanBERT: A Hanzi-aware Pre-trained Language Model for Chinese Biomedical Text Mining. 1415-1420 - Bang Wu, Xiangwen Yang, Shirui Pan, Xingliang Yuan:
Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications. 1421-1426 - Daqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Pengfei Wang, Minghua Deng, Jinwen Ma:
Composition-Enhanced Graph Collaborative Filtering for Multi-behavior Recommendation. 1427-1432 - Yanzhao Wu, Ling Liu:
Boosting Deep Ensemble Performance with Hierarchical Pruning. 1433-1438 - Le Xu, Lei Cheng, Ngai Wong, Yik-Chung Wu:
Overfitting Avoidance in Tensor Train Factorization and Completion: Prior Analysis and Inference. 1439-1444 - Hao Yang, Min Wang, Yun Zhou, Yongxin Yang:
Towards Stochastic Neural Network via Feature Distribution Calibration. 1445-1450 - Qingping Yang, Yingpeng Hu, Rongyu Cao, Hongwei Li, Ping Luo:
Zero-shot Key Information Extraction from Mixed-Style Tables: Pre-training on Wikipedia. 1451-1456 - Jui-Nan Yen, Chih-Jen Lin:
Limited-memory Common-directions Method With Subsampled Newton Directions for Large-scale Linear Classification. 1457-1462 - Miao Yu, Wenbin Lu, Rui Song:
Online Testing of Subgroup Treatment Effects Based on Value Difference. 1463-1468 - Li Zhang, Shitian Shen, Lingxiao Li, Han Wang, Xueying Li, Jun Lang:
Jointly Multi-Similarity Loss for Deep Metric Learning. 1469-1474 - Mingyang Zhang, Yong Li, Funing Sun, Diansheng Guo, Pan Hui:
Adaptive Spatio-Temporal Convolutional Network for Traffic Prediction. 1475-1480 - Shuai Zhang, Jianxin Li, Haoyi Zhou, Qishan Zhu, Shanghang Zhang, Danding Wang:
MERITS: Medication Recommendation for Chronic Disease with Irregular Time-Series. 1481-1486 - Wang Zhang, Yang Yu, Ting Pan, Lin Pan, Pengfei Jiao, Wenjun Wang:
Generating Structural Node Representations via Higher-order Features and Adversarial Learning. 1487-1492 - Xu Zhang, Liang Zhang, Bo Jin, Xinjiang Lu:
A Multi-view Confidence-calibrated Framework for Fair and Stable Graph Representation Learning. 1493-1498 - Yanfu Zhang, Lei Luo, Heng Huang:
Unified Fairness from Data to Learning Algorithm. 1499-1504 - Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, Jun Luo:
C3-GAN: Complex-Condition-Controlled Urban Traffic Estimation through Generative Adversarial Networks. 1505-1510 - Zhao-Yu Zhang, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values. 1511-1516 - Zizhuo Zhang, Bang Wang:
Graph Neighborhood Routing and Random Walk for Session-based Recommendation. 1517-1522 - Li Zheng, Jun Gao, Zhao Li, Ji Zhang:
AdaBoosting Clusters on Graph Neural Networks. 1523-1528 - Cangqi Zhou, Jinling Shang, Jing Zhang, Qianmu Li, Dianming Hu:
Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase Generation. 1529-1534 - Dongming Zhou, Jing Yang, Canlong Zhang, Yanping Tang:
Joint Scence Network and Attention-Guided for Image Captioning. 1535-1540 - Fan Zhou, Chenfan Lu, Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Jieping Ye, Hongtu Zhu:
Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching. 1541-1546 - Ronghang Zhu, Sheng Li:
Self-supervised Universal Domain Adaptation with Adaptive Memory Separation. 1547-1552 - Xiaoyan Zhu, Ting Wang, Jiayin Wang, Ying Xu, Yuqian Liu:
A new multiple instance algorithm using structural information. 1553-1558 - Xunyu Zhu, Jian Li, Yong Liu, Jun Liao, Weiping Wang:
Operation-level Progressive Differentiable Architecture Search. 1559-1564 - Jingwei Zuo, Karine Zeitouni, Yehia Taher:
SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series. 1565-1570
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