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ORCID22nd SDM 2022: Alexandria, VA, USA
- Arindam Banerjee, Zhi-Hua Zhou, Evangelos E. Papalexakis, Matteo Riondato
:
Proceedings of the 2022 SIAM International Conference on Data Mining, SDM 2022, Alexandria, VA, USA, April 28-30, 2022. SIAM 2022, ISBN 978-1-61197-717-2 - Ronghang Zhu, Sheng Li:
Self-supervision based Semantic Alignment for Unsupervised Domain Adaptation. 1-9 - Chang Liu, Lichen Wang, Yun Fu:
Meta Adversarial Weight for Unsupervised Domain Adaptation. 10-18 - Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Elke A. Rundensteiner, Emmanuel Agu:
Positive Unlabeled Learning with a Sequential Selection Bias. 19-27 - Fred Lu, Francis Ferraro, Edward Raff:
Continuously Generalized Ordinal Regression for Linear and Deep Models. 28-36 - Wen Gu, Teng Zhang, Hai Jin:
Entropy Weight Allocation: Positive-unlabeled Learning via Optimal Transport. 37-45 - Hiroyoshi Ito, Christos Faloutsos:
DualCast: Friendship-Preference Co-evolution Forecasting for Attributed Networks. 46-54 - Meng Liu, Shuiwang Ji:
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. 55-63 - Xiaolin Han, Reynold Cheng, Tobias Grubenmann, Silviu Maniu, Chenhao Ma, Xiaodong Li:
Leveraging Contextual Graphs for Stochastic Weight Completion in Sparse Road Networks. 64-72 - Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Interpretable Molecular Graph Generation via Monotonic Constraints. 73-81 - Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu:
Structure-Enhanced Heterogeneous Graph Contrastive Learning. 82-90 - Xiaowei Jia, Shengyu Chen, Yiqun Xie, Haoyu Yang, Alison P. Appling, Samantha Oliver, Zhe Jiang:
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature. 91-99 - Guangyu Meng, Qisheng Jiang, Kaiqun Fu, Beiyu Lin, Chang-Tien Lu, Zhqian Chen:
Early Forecasting of the Impact of Traffic Accidents Using a Single Shot Observation. 100-108 - Qianru Zhang, Zheng Wang, Cheng Long, Siu-Ming Yiu:
On Predicting and Generating a Good Break Shot in Billiards Sports. 109-117 - Hao Sun, Yuntao Li, Yan Zhang:
ConLearn: Contextual-knowledge-aware Concept Prerequisite Relation Learning with Graph Neural Network. 118-126 - Derun Cai, Chenxi Sun, Moxian Song, Baofeng Zhang, Shenda Hong, Hongyan Li:
Hypergraph Contrastive Learning for Electronic Health Records. 127-135 - Maxwell McNeil, Boya Ma, Petko Bogdanov:
SAGA: Signal-Aware Graph Aggregation. 136-144 - Ilya Amburg, Nate Veldt, Austin R. Benson:
Diverse and Experienced Group Discovery via Hypergraph Clustering. 145-153 - Jaemin Yoo, Lee Sael:
Transition Matrix Representation of Trees with Transposed Convolutions. 154-162 - Hyunjin Choo, Kijung Shin:
On the Persistence of Higher-Order Interactions in Real-World Hypergraphs. 163-171 - Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen:
Neural Graph Matching for Pre-training Graph Neural Networks. 172-180 - Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Wei Zhang, Eamonn J. Keogh:
Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series. 181-189 - Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima:
Learning Time-series Shapelets Enhancing Discriminability. 190-198 - Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Towards Similarity-Aware Time-Series Classification. 199-207 - Li Zhang, Nital Patel, Xiuqi Li, Jessica Lin:
Joint Time Series Chain: Detecting Unusual Evolving Trend across Time Series. 208-216 - Grace Deng, Cuize Han, Tommaso Dreossi, Clarence Lee, David S. Matteson:
IB-GAN: A Unified Approach for Multivariate Time Series Classification under Class Imbalance. 217-225 - Collin Leiber, Dominik Mautz, Claudia Plant, Christian Böhm:
Automatic Parameter Selection for Non-Redundant Clustering. 226-234 - Maximilian Schier, Christoph Reinders, Bodo Rosenhahn:
Constrained Mean Shift Clustering. 235-243 - Yixuan He, Gesine Reinert, Songchao Wang, Mihai Cucuringu:
SSSNET: Semi-Supervised Signed Network Clustering. 244-252 - Yongliang Ding, Tao Zhou, Chuang Zhang, Yijing Luo, Juan Tang, Chen Gong:
Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation. 253-261 - Shuang Zhou, Xiao Huang, Ninghao Liu, Qiaoyu Tan, Fu-Lai Chung:
Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning. 262-270 - Wenming Jiang, Ying Zhao, Yihan Wu, Haojia Zuo:
Capturing Model Uncertainty with Data Augmentation in Deep Learning. 271-279 - Stefan Oehmcke, Fabian Gieseke:
Input Selection for Bandwidth-Limited Neural Network Inference. 280-288 - Pratik Mandlecha, Snehith Kumar Chatakonda, Neeraj Kollepara, Pawan Kumar:
Hybrid Tokenization and Datasets for Solving Mathematics and Science Problems Using Transformers. 289-297 - Yishuo Zhang, Nayyar Abbas Zaidi, Jiahui Zhou, Gang Li:
GANBLR++: Incorporating Capacity to Generate Numeric Attributes and Leveraging Unrestricted Bayesian Networks. 298-306 - Jiahui Wei, Zhixin Li, Jianwei Zhu, Huifang Ma:
Flexible Image Captioning via Internal Understanding and External Reasoning. 307-315 - Wei-Lun Luo, Yu-Ming Lu, Jheng-Hong Yang, Jin-Chuan Duan, Chuan-Ju Wang:
Multiperiod Corporate Default Prediction Through Neural Parametric Family Learning. 316-324 - Arnaud Pannatier, Ricardo Picatoste, François Fleuret:
Efficient Wind Speed Nowcasting with GPU-Accelerated Nearest Neighbors Algorithm. 325-333 - Bang An, Amin Vahedian, Xun Zhou, W. Nick Street, Yanhua Li:
HintNet: Hierarchical Knowledge Transfer Networks for Traffic Accident Forecasting on Heterogeneous Spatio-Temporal Data. 334-342 - Vishu Gupta, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal:
BRNet: Branched Residual Network for Fast and Accurate Predictive Modeling of Materials Properties. 343-351 - Tianqi Wang, Fenglong Ma, Tang Tang, Longfei Zhang, Jing Gao:
Textbook Enhanced Student Learning Outcome Prediction. 352-360 - Tianyi Chen, Francesco Bonchi, David García-Soriano, Atsushi Miyauchi, Charalampos E. Tsourakakis:
Dense and well-connected subgraph detection in dual networks. 361-369 - Zhao Kang, Zhanyu Liu, Shirui Pan, Ling Tian:
Fine-grained Attributed Graph Clustering. 370-378 - Daniel Ferguson, François G. Meyer:
Computation of the Sample Fréchet Mean for Sets of Large Graphs with Applications to Regression. 379-387 - Andrew Stolman, Caleb C. Levy, C. Seshadhri, Aneesh Sharma:
Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling. 388-396 - Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang:
HG-Meta: Graph Meta-learning over Heterogeneous Graphs. 397-405 - Caiqi Sun, Penghao Lu, Lei Cheng, Zhenfu Cao, Xiaolei Dong, Yili Tang, Jun Zhou, Linjian Mo:
Multi-interest Sequence Modeling for Recommendation with Causal Embedding. 406-414 - Alexander Marx, Jonas Fischer:
Estimating Mutual Information via Geodesic kNN. 415-423 - Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang:
Masked Gradient-Based Causal Structure Learning. 424-432 - Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data. 433-441 - Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu:
Cycle-Balanced Representation Learning For Counterfactual Inference. 442-450 - Yen-hsiu Chou, Shenda Hong, Chenxi Sun, Derun Cai, Moxian Song, Hongyan Li:
GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization. 451-458 - Koji Matsuda, Yuya Sasaki, Chuan Xiao, Makoto Onizuka:
FedMe: Federated Learning via Model Exchange. 459-467 - Yingxue Zhou, Xinyan Li, Arindam Banerjee:
Noisy Truncated SGD: Optimization and Generalization. 468-476 - Dzung T. Phan, Hongsheng Liu, Lam M. Nguyen:
StepDIRECT - A Derivative-Free Optimization Method for Stepwise Functions. 477-485 - Xiangyu Li, Hua Wang:
Adaptive Principal Component Analysis. 486-494 - Yue Bai, Zhiqiang Tao, Lichen Wang, Sheng Li, Yu Yin, Yun Fu:
Collaborative Attention Mechanism for Multi-Modal Time Series Classification. 495-503 - Shoumik Roychoudhury, Fang Zhou, Zoran Obradovic:
Leveraging Dependencies among Learned Temporal Subsequences. 504-512 - Alexandra Iacob, Bogdan Cautis, Silviu Maniu:
Contextual Bandits for Advertising Campaigns: A Diffusion-Model Independent Approach. 513-521 - Sichen Zhao, Wei Shao, Jeffrey Chan, Flora D. Salim:
Measuring disentangled generative spatio-temporal representation. 522-530 - Keke Zhao, Xing Zhao, Qi Cao, Linjian Mo:
A Non-sequential Approach to Deep User Interest Model for CTR Prediction. 531-539 - Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie, Jiliang Tang:
Localized Graph Collaborative Filtering. 540-548 - Ryoma Sato:
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? 549-557 - Zhikai Wang, Yanyan Shen:
Time-aware Multi-interest Capsule Network for Sequential Recommendation. 558-566 - Xuelian Ni, Fei Xiong, Yutian Hu, Shirui Pan, Hongshu Chen, Liang Wang:
Cyclic Transfer Learning for Recommender Systems with Heterogeneous Feedbacks. 567-575 - Haoliang Liu, Tan Yu, Ping Li:
Sensitivity-aware Distance Measurement for Boosting Metric Learning. 576-584 - Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy:
Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS). 585-593 - Wentao Wang, Joseph Thekinen, Xiaorui Liu, Zitao Liu, Jiliang Tang:
Learning from Imbalanced Crowdsourced Labeled Data. 594-602 - Jun Zhuang, Mohammad Al Hasan:
Deperturbation of Online Social Networks via Bayesian Label Transition. 603-611 - Qi Qian, Hao Li, Juhua Hu:
Improved Knowledge Distillation via Full Kernel Matrix Transfer. 612-620 - Eitan Kosman, Ilya Kolchinsky, Assaf Schuster:
Mining Logical Arithmetic Expressions From Proper Representations. 621-629 - Adithya Kulkarni, Nasim Sabetpour, Alexey Markin, Oliver Eulenstein, Qi Li:
CPTAM: Constituency Parse Tree Aggregation Method. 630-638 - Hafsa Ennajari, Nizar Bouguila, Jamal Bentahar:
Knowledge-enhanced Spherical Representation Learning for Text Classification. 639-647 - Farimah Poursafaei, Zeljko Zilic, Reihaneh Rabbany:
A Strong Node Classification Baseline for Temporal Graphs. 648-656 - Yujie Fan, Mingxuan Ju, Chuxu Zhang, Yanfang Ye:
Heterogeneous Temporal Graph Neural Network. 657-665 - Yiming Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang:
Adapting Distilled Knowledge for Few-shot Relation Reasoning over Knowledge Graphs. 666-674 - Yue Zhang, Mingming Sun, Jingyuan Zhang, Ping Li:
Explainable Concept Graph Completion by Bridging Open-Domain Relations and Concepts. 675-683 - Shweta Jain, Hanghang Tong:
YACC: A Framework Generalizing TuránShadow for Counting Large Cliques. 684-692 - Lingwei Chen, Xiaoting Li, Dinghao Wu:
Adversarially Reprogramming Pretrained Neural Networks for Data-limited and Cost-efficient Malware Detection. 693-701 - Kshitij Tayal, Xiaowei Jia, Rahul Ghosh, Jared Willard, Jordan S. Read, Vipin Kumar:
Invertibility aware Integration of Static and Time-series data: An application to Lake Temperature Modeling. 702-710 - Pengfei Wang, Kunpeng Liu, Yuanchun Zhou, Yanjie Fu:
Unifying Human Mobility Forecasting and Trajectory Semantics Augmentation via Hawkes Process Based LSTM. 711-719 - Thai-Hoang Pham, Lei Xie, Ping Zhang:
FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery. 720-728 - Shrimon Mukherjee, Madhusudan Ghosh, Partha Basuchowdhuri:
DeepGLSTM: Deep Graph Convolutional Network and LSTM based approach for predicting drug-target binding affinity. 729-737
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