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ORCID23rd SDM 2023: Minneapolis-St. Paul Twin Cities, MN, USA
- Shashi Shekhar, Zhi-Hua Zhou, Yao-Yi Chiang, Gregor Stiglic:
Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023. SIAM 2023, ISBN 978-1-61197-765-3 - Maxwell McNeil, Carolina Mattsson, Frank W. Takes, Petko Bogdanov:
CADENCE: Community-Aware Detection of Dynamic Network States. 1-9 - Peiyan Li
, Honglian Wang, Kai Li, Christian Böhm:
Influence without Authority: Maximizing Information Coverage in Hypergraphs. 10-18 - Lutz Oettershagen, Nils M. Kriege, Claude Jordan, Petra Mutzel:
A Temporal Graphlet Kernel For Classifying Dissemination in Evolving Networks. 19-27 - Dezhi Yang, Guoxian Yu, Jun Wang, Zhongmin Yan, Maozu Guo:
Causal Discovery by Graph Attention Reinforcement Learning. 28-36 - Jianxiang Yu, Xiang Li:
Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Weighted Negative Samples. 37-45 - Xiaoyang Liu, Chong Liu, Pinzheng Wang, Rongqin Zheng, Lixin Zhang, Leyu Lin, Zhijun Chen, Liangliang Fu:
UFNRec: Utilizing False Negative Samples for Sequential Recommendation. 46-54 - Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu:
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. 55-63 - Lu Wang, Yuhai Song, Zhe Wang, Haoxiang Wang, Yu Li, Weiwei Zhou, Haoming Dang, Mona Shao, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao:
Pluggable Deep Thompson Sampling with Applications to Recommendation. 64-72 - Shilei Cao, Yujie Lin, Xianli Zhang, Yufu Chen, Zhen Zhu, Yuxin Chen, Buyue Qian, Feng Wang, Zang Li:
Embedding Transfer with Enhanced Correlation Modeling for Cross-Domain Recommendation. 73-81 - Ravdeep S. Pasricha, Uday Singh Saini, Nicholas D. Sidiropoulos, Fei Fang, Kevin Chan, Evangelos E. Papalexakis:
Harvester: Principled Factorization-based Temporal Tensor Granularity Estimation. 82-90 - Yanhao Wang, Michael Mathioudakis, Jia Li, Francesco Fabbri:
Max-Min Diversification with Fairness Constraints: Exact and Approximation Algorithms. 91-99 - Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini:
Beyond The Evidence Lower Bound: Dual Variational Graph Auto-Encoders For Node Clustering. 100-108 - Lena G. M. Bauer, Collin Leiber, Christian Böhm, Claudia Plant:
Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering. 109-117 - Joshua Tobin, Chin Pang Ho, Mimi Zhang:
Reinforced EM Algorithm for Clustering with Gaussian Mixture Models. 118-126 - Rodrigo Randel, Daniel Aloise, Alain Hertz:
A Lagrangian-based approach to learn distance metrics for clustering with minimal data transformation. 127-135 - Zehong Wang, Qi Li, Donghua Yu, Xiaolong Han, Xiao-Zhi Gao, Shigen Shen:
Heterogeneous Graph Contrastive Multi-view Learning. 136-144 - Jingyou Xie, Zishuo Zhao, Zhenzhou Lin, Ying Shen:
Multimodal Graph Learning for Cross-Modal Retrieval. 145-153 - Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li:
RELIANT: Fair Knowledge Distillation for Graph Neural Networks. 154-162 - Senzhang Wang, Hao Yan, Jinlong Du, Jun Yin, Junxing Zhu, Chaozhuo Li, Jianxin Wang:
Adversarial Hard Negative Generation for Complementary Graph Contrastive Learning. 163-171 - Dominic Jack, Sarah M. Erfani, Jeffrey Chan, Sutharshan Rajasegarar, Christopher Leckie:
It's PageRank All The Way Down: Simplifying Deep Graph Networks. 172-180 - Sikun Yang, Hongyuan Zha:
Estimating Latent Population Flows from Aggregated Data via Inversing Multi-Marginal Optimal Transport. 181-189 - Zhengyang Zhou, Kuo Yang, Wei Sun, Binwu Wang, Min Zhou, Yunan Zong, Yang Wang:
Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics. 190-198 - Junyang Chen, Yidan Dai, Xianhui Chen, Yingshan Shen, Yan Luximon, Hailiang Wang, Yuxin He, Wenjun Ma, Xiaomao Fan:
StAGN: Spatial-Temporal Adaptive Graph Network via Contrastive Learning for Sleep Stage Classification. 199-207 - Yingxue Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, Jun Luo:
STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies. 208-216 - Shengyu Chen, Yiqun Xie, Xiang Li, Xu Liang, Xiaowei Jia:
Physics-Guided Meta-Learning Method in Baseflow Prediction over Large Regions. 217-225 - Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang:
ML4C: Seeing Causality Through Latent Vicinity. 226-234 - Mansoureh Maadi, Hadi Akbarzadeh Khorshidi, Uwe Aickelin:
Uncertainty in Selective Bagging: A Dynamic Bi-objective Optimization Model. 235-243 - Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao:
Saliency-Augmented Memory Completion for Continual Learning. 244-252 - Jonatan Møller Nuutinen Gøttcke, Colin Bellinger, Paula Branco, Arthur Zimek:
An Interpretable Measure of Dataset Complexity for Imbalanced Classification Problems. 253-261 - Shuai Feng, Wenyu Jiang, Mingcai Chen, Yuntao Du, Hao Cheng, Yuxin Ge, Chongjun Wang:
CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection. 262-270 - Kimia Shayestehfard, Dana H. Brooks, Stratis Ioannidis:
AlignGraph: A Group of Generative Models for Graphs. 271-279 - Lutz Oettershagen, Petra Mutzel:
An Index For Temporal Closeness Computation in Evolving Graphs. 280-288 - Giulia Punzi, Alessio Conte, Roberto Grossi, Andrea Marino:
An Efficient Algorithm for Assessing the Number of st-Paths in Large Graphs. 289-297 - Si Zhang, Yinglong Xia, Yan Zhu, Hanghang Tong:
Representation Learning on Dynamic Network of Networks. 298-306 - Huiping Chen, Grigorios Loukides, Robert Gwadera, Solon P. Pissis:
Heavy Nodes in a Small Neighborhood: Algorithms and Applications. 307-315 - Zhe Jiang, Yupu Zhang, Saugat Adhikari, Da Yan, Arpan Man Sainju, Xiaowei Jia, Yiqun Xie:
A Hidden Markov Forest Model for Terrain-Aware Flood Inundation Mapping from Earth Imagery. 316-324 - Hao Niu, Guillaume Habault, Roberto Legaspi, Chuizheng Meng, Defu Cao, Shinya Wada, Chihiro Ono, Yan Liu:
Time-delayed Multivariate Time Series Predictions. 325-333 - Zheng Chen, Lingwei Zhu, Haohui Jia, Takashi Matsubara:
A Two-View EEG Representation for Brain Cognition by Composite Temporal-Spatial Contrastive Learning. 334-342 - Pengfei Wang, Daniel Wang, Kunpeng Liu, Dongjie Wang, Yuanchun Zhou, Leilei Sun, Yanjie Fu:
Hierarchical Reinforced Urban Planning: Jointly Steering Region and Block Configurations. 343-351 - Boris Wiegand, Dietrich Klakow, Jilles Vreeken:
Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times. 352-360 - Xiaowei Jia, Shengyu Chen, Can Zheng, Yiqun Xie, Zhe Jiang, Nasrin Kalanat:
Physics-guided Graph Diffusion Network for Combining Heterogeneous Simulated Data: An Application in Predicting Stream Water Temperature. 361-369 - Litian Zhang, Xiaoming Zhang, Ziming Guo, Zhipeng Liu:
CISum: Learning Cross-modality Interaction to Enhance Multimodal Semantic Coverage for Multimodal Summarization. 370-378 - Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel:
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction. 379-387 - Ziheng Zhou, Ying Zhao, Yiyu Qing, Wenming Jiang, Yihan Wu, Wenguang Chen:
A Physics-guided NN-based Approach for Tropical Cyclone Intensity Estimation. 388-396 - Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu:
Anomaly Detection Networks and Fuzzy Control Modules for Energy Grid Management with Q-Learning-Based Decision Making. 397-405 - David Liu, Tina Eliassi-Rad:
STABLE: Identifying and Mitigating Instability in Embeddings of the Degenerate Core. 406-414 - Chamalee Wickrama Arachchi, Nikolaj Tatti:
Node ranking in labeled networks. 415-423 - Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang:
Optimal Intervention on Weighted Networks via Edge Centrality. 424-432 - Boya Ma, Maxwell McNeil, Petko Bogdanov:
GIST: Graph Inference for Structured Time Series. 433-441 - Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi:
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. 442-450 - Jana Holznigenkemper, Christian Komusiewicz, Bernhard Seeger:
Exact and Heuristic Approaches to Speeding Up the MSM Time Series Distance Computation. 451-459 - Zhuoqun Li, Zihan Zhou, Mingxuan Sun, Hongteng Xu:
Debiased Imitation Learning for Modulated Temporal Point Processes. 460-468 - Khandakar Tanvir Ahmed, Sudipto Baul, Yanjie Fu, Wei Zhang:
Attention-Based Multi-modal Missing Value Imputation for Time Series Data with High Missing Rate. 469-477 - Junlong Tong, Liping Xie, Kanjian Zhang:
Probabilistic Decomposition Transformer for Time Series Forecasting. 478-486 - Praveen Ravirathinam, Rahul Ghosh, Ke Wang, Keyang Xuan, Ankush Khandelwal, Hilary Dugan, Paul C. Hanson, Vipin Kumar:
Spatiotemporal Classification with limited labels using Constrained Clustering for large datasets. 487-495 - Jiaqi Wang, Shenglai Zeng, Zewei Long, Yaqing Wang, Houping Xiao, Fenglong Ma:
Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT. 496-504 - Xiangping Zheng, Xun Liang, Bo Wu, Jun Wang, Yuhui Guo, Xuan Zhang, Yuefeng Ma:
A Multi-scale Interaction Motion Network for Action Recognition Based on Capsule Network. 505-513 - Zerun Lin, Yuhan Zhang, Lixin Duan, Le Ou-Yang, Peilin Zhao:
MoVAE: A Variational AutoEncoder for Molecular Graph Generation. 514-522 - Tian Xia, Sarp Aykent, Wei-Shinn Ku:
Extrinsic-Intrinsic Representation Learning Framework for Drug Discovery. 523-531 - Jan Gertheiss, Russell T. Shinohara:
Penalized Non-Linear Canonical Correlation Analysis for Ordinal Data with Application to the International Classification of Functioning, Disability and Health. 532-540 - Xin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang:
Domain Disentangled Meta-Learning. 541-549 - Shan Lu, Mingjun Zhao, Songling Yuan, Xiaoli Wang, Lei Yang, Di Niu:
BDA: Bandit-based Transferable AutoAugment. 550-558 - Lorenz Kummer, Kevin Sidak, Tabea Reichmann, Wilfried N. Gansterer:
Adaptive Precision Training (AdaPT): A dynamic quantized training approach for DNNs. 559-567 - Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
Robust Learning via Golden Symmetric Loss of (un)Trusted Labels. 568-576 - Shengyu Feng, Hanghang Tong:
Concept Discovery for Fast Adaptation. 577-585 - Mengyuan Zhang, Kai Liu:
Multi-Task Learning with Prior Information. 586-594 - Peng Liu, Yi Liu, Rui Zhu, Linglong Kong, Bei Jiang, Di Niu:
Optimal Smooth Approximation for Quantile Matrix Factorization. 595-603 - Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Ranking with submodular functions on the fly. 604-612 - Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou:
Learning Causal Structure on Mixed Data with Tree-Structured Functional Models. 613-621 - Zahra Donyavi, Adriane Serapio, Gustavo Batista:
MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification. 622-630 - Jinfeng Xiao, Mohab Elkaref, Nathan Herr, Geeth De Mel, Jiawei Han:
Taxonomy-Guided Fine-Grained Entity Set Expansion. 631-639 - Karan Vombatkere, Evimaria Terzi:
Balancing Task Coverage and Expert Workload in Team Formation. 640-648 - Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications. 649-657 - Huafeng Yang, Qijie Shen, Xingjian Chen, Fangyi Zhang, Rong Du:
A Linkage-based Doubly Imbalanced Graph Learning Framework for Face Clustering. 658-666 - Xu Ye, Meng Xiao, Zhiyuan Ning, Weiwei Dai, Wenjuan Cui, Yi Du, Yuanchun Zhou:
NEEDED: Introducing Hierarchical Transformer to Eye Diseases Diagnosis. 667-675 - Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. 676-684 - Sadaf Tafazoli, Eamonn J. Keogh:
Matrix Profile XXVIII: Discovering Multi-Dimensional Time Series Anomalies with K of N Anomaly Detection†. 685-693 - Rui Wang, Chongwei Liu, Xudong Mou, Kai Gao, Xiaohui Guo, Pin Liu, Tianyu Wo, Xudong Liu:
Deep Contrastive One-Class Time Series Anomaly Detection. 694-702 - Zhong Zhuang, Kai Ming Ting, Guansong Pang, Shuaibin Song:
Subgraph Centralization: A Necessary Step for Graph Anomaly Detection. 703-711 - Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. 712-720 - Fred X. Han, Keith G. Mills, Fabian Chudak, Parsa Riahi, Mohammad Salameh, Jialin Zhang, Wei Lu, Shangling Jui, Di Niu:
A General-Purpose Transferable Predictor for Neural Architecture Search. 721-729 - Zhixuan Chu, Mechelle Claridy, José Cordero, Sheng Li, Stephen L. Rathbun:
Estimating Propensity Scores with Deep Adaptive Variable Selection. 730-738 - Aleksandr Rubashevskii, Daria Kotova, Maxim Panov:
Scalable Batch Acquisition for Deep Bayesian Active Learning. 739-747 - Jackson de Faria, Renato Assunção, Fabricio Murai:
Fisher Scoring Method for Neural Networks Optimization. 748-756 - Md Mahmudur Rahman, Sanjay Purushotham:
Multi-state Survival Analysis using Pseudo value-based Deep Neural Networks. 757-765 - Zonghan Zhang, Zhiqian Chen:
Understanding Influence Maximization via Higher-Order Decomposition. 766-774 - Meng Xiao, Dongjie Wang, Min Wu, Ziyue Qiao, Pengfei Wang, Kunpeng Liu, Yuanchun Zhou, Yanjie Fu:
Traceable Automatic Feature Transformation via Cascading Actor-Critic Agents. 775-783 - Guangtao Zheng, Qiuling Suo, Mengdi Huai, Aidong Zhang:
Learning to Learn Task Transformations for Improved Few-Shot Classification. 784-792 - Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Cristina L. Abad, Carmen Vaca:
Sign-Regularized Multi-Task Learning. 793-801 - Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble:
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. 802-810 - Ziqiao Meng, Yaoman Li, Peilin Zhao, Yang Yu, Irwin King:
Meta-Learning with Motif-based Task Augmentation for Few-Shot Molecular Property Prediction. 811-819 - Dries Van der Plas, Wannes Meert, Johan Verbraecken, Jesse Davis:
A novel reject option applied to sleep stage scoring. 820-828 - Yuhu Shang, Xuexiong Luo, Lihong Wang, Hao Peng, Xiankun Zhang, Yimeng Ren, Kun Liang:
Reinforcement Learning Guided Multi-Objective Exam Paper Generation. 829-837 - Yan Li, Mingzhou Yang, Matthew Eagon, Majid Farhadloo, Yiqun Xie, William F. Northrop, Shashi Shekhar:
Eco-PiNN: A Physics-informed Neural Network for Eco-toll Estimation. 838-846 - Somya Sharma, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher J. Duffy, Vipin Kumar:
Probabilistic Inverse Modeling: An Application in Hydrology. 847-855 - Lecheng Zheng, Yada Zhu, Jingrui He:
Fairness-aware Multi-view Clustering. 856-864 - Zhiyu Xue:
Group AdaBoost with Fairness Constraint. 865-873 - Yan Zhou, Murat Kantarcioglu, Chris Clifton:
On Improving Fairness of AI Models with Synthetic Minority Oversampling Techniques. 874-882 - Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan, Ke Wang:
TEM: High Utility Metric Differential Privacy on Text. 883-890 - Li Zhang, Jiahao Ding, Yifeng Gao, Jessica Lin:
PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series. 891-899 - Xuechen Zhao, Jiaying Zou, Zhong Zhang, Feng Xie, Bin Zhou, Lei Tian:
Feature Enhanced Zero-Shot Stance Detection via Contrastive Learning. 900-908 - Xiusi Chen, Yu Zhang, Jinliang Deng, Jyun-Yu Jiang, Wei Wang:
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. 909-917 - Tingxin Li, Rui Meng, Feng Chen, Jianming Wu:
Coarse-to-Fine Open Information Extraction via Relation Oriented Reading Comprehension. 918-926 - Saed Rezayi, Handong Zhao, Ronghang Zhu, Sheng Li:
XDC: Adaptive Cross Domain Short Text Clustering. 927-935 - Ningjing Wang, Deqing Wang, Ting Jiang, Chenguang Du, Chuyu Fang, Fuzhen Zhuang:
Hierarchical Neural Topic Model with Embedding Cluster and Neural Variational Inference. 936-944 - Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Xia Hu:
Data-centric AI: Perspectives and Challenges. 945-948 - Matteo Riondato:
Statistically-sound Knowledge Discovery from Data. 949-952 - Mingzhou Yang, Bharat Jayaprakash, Matthew Eagon, Hyeonjung (Tari) Jung, William F. Northrop, Shashi Shekhar:
Data Mining Challenges and Opportunities to Achieve Net Zero Carbon Emissions: Focus on Electrified Vehicles. 953-956 - Sheng Li:
Towards Trustworthy Representation Learning. 957-960 - Nripsuta Ani Saxena, Wenbin Zhang, Cyrus Shahabi:
Missed Opportunities in Fair AI. 961-964 - Dell Zhang, Frank Schilder, Jack G. Conrad, Masoud Makrehchi, David von Rickenbach, Isabelle Moulinier:
Making a Computational Attorney. 965-968
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