Accepted Papers

Decision notifications to authors were sent out via email on 31 August. Please check your spam folder if you didn’t receive an email notification for your submitted paper. You can also access your reviews via Cyberchair. Accepted papers are listed below.

 

Regular Papers

DM277 “Structure-Aware Stabilization of Adversarial Robustness with Massive Contrastive Adversaries”
Shuo Yang, Zeyu Feng, Pei Du, Bo Du, and Chang Xu

DM286 “Physics Interpretable Shallow-Deep NeuralNetworks for Physical System Identification withUnobservability”
Jingyi Yuan and Yang Weng

DM360 “Dictionary Pair-based Data-Free Fast Deep Neural Network Compression”
Yangcheng Gao, Zhao Zhang, Haijun Zhang, Mingbo Zhao, Yang Yi, and Meng Wang

DM363 “BaT: a Beat-aligned Transformer for Electrocardiogram”
Xiaoyu Li, Chen Li, Yuhua Wei, Yuyao Sun, Jishang Wei, Xiang Li, and Buyue Qian

DM374 “Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences”
Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, and Bin Wang

DM389 “Flexible, Robust, Scalable Semi-supervised Learning via Reliability Propagation”
Chen Huang, Liangxu Pan, Qinli Yang, Hongliang Wang, and Junming Shao

DM424 “Robustifying DARTS by Eliminating Information Bypass Leakage via Explicit Sparse Regularization”
Jiuling Zhang and Zhiming Ding

DM435 “Accurate Graph-Based PU Learning without Class Prior”
Jaemin Yoo, Junghun Kim, Hoyoung Yoon, Geonsoo Kim, Changwon Jang, and U Kang

DM441 “Triplet Deep Subspace Clustering via Self-Supervised Data Augmentation”
Zhao Zhang, Xianzhen Li, Haijun Zhang, Yi Yang, Shuicheng Yan, and Meng Wang

DM452 “LAGA: Lagged AllReduce with Gradient Accumulation for Minimal Idle Time”
Ido Hakimi, Rotem Zamir Aviv, Kfir Yehuda Levy, and Assaf Schuster

DM455 “Highly Scalable and Provably Accurate Classification in Poincar\’e Balls”
Eli Chien, Chao Pan, Puoya Tabaghi, and Olgica Milenkovic

DM461 “A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity”
Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, and Praveen Ravirathinam

DM462 “Graph Transfer Learning”
Andrey Gritsenko, Yuan Guo, Kimia Shayestehfard, Armin Moharrer, Jennifer Dy, and Stratis Ioannidis

DM468 “Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation”
Haoran Yang, Hongxu Chen, Lin Li, Philip S. Yu, and Guandong Xu

DM474 “Adversarial Online Kernel Learning with Application on Graphs”
Peng Yang, Xiaoyun Li, and Ping Li

DM484 “AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks”
Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, and Jiawei Han

DM486 “Attention-based Feature Interaction for Efficient Online Knowledge Distillation”
Tongtong Su, Qiyu Liang, Jinsong Zhang, Zhaoyang Yu, Gang Wang, and Xiaoguang Liu

DM505 “Differentially Private String Sanitization for Frequency-Based Mining Tasks”
Huiping Chen, Changyu Dong, Liyue Fan, Grigorios Loukides, Solon Pissis, and Leen Stougie

DM535 “Truth Discovery in Sequence Labels from Crowds”
Nasim Sabetpour, Adithya Kulkarni, Sihong Xie, and Qi Li

DM540 “GraphANGEL: Adaptive and Structure-Aware Sampling on Graph Neural Networks”
Jingshu Peng, Yanyan Shen, and Lei Chen

DM544 “Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings”
Yuandu Lai, Yahong Han, and Yaowei Wang

DM559 “Multi-objective Explanations of GNN Predictions”
Yifei Liu, Chao Chen, Yazheng Liu, Xi Zhang, and Sihong Xie

DM566 “Mcore: Multi-Agent Collaborative Learning for Knowledge-Graph-Enhanced Recommendation”
Xujia Li, Yanyan Shen, and Lei Chen

DM571 “DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction”
Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, and Jun Luo

DM580 “Sequential Diagnosis Prediction with Transformer and Ontological Representation”
Xueping Peng, Guodong Long, Tao Shen, Sen Wang, and Jing Jiang

DM603 “Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature”
Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, and Taylor Johnson

DM616 “Robust Low-rank Deep Feature Recovery in CNNs: Toward Low Information Loss and Fast Convergence”
Jiahuan Ren, Zhao Zhang, Jicong Fan, Haijun Zhang, Mingliang Xu, and Meng Wang

DM619 “Better Prevent than React: Deep Stratified Learning to Predict Hate Intensity of Twitter Reply Chains”
Dhruv Sahnan, Snehil Dahiya, Vasu Goel, Anil Bandhakavi, and Tanmoy Chakraborty

DM628 “Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems”
Xiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, and Jordan Read

DM629 “HGEN: Deep Heterogeneous Graph Generation”
Chen Ling, Carl Yang, and Liang Zhao

DM632 “Isolation Kernel Density Estimation”
Kai Ming Ting, Takashi Washio, Jonathan Wells, and Hang Zhang

DM640 “Outlier-Robust Multi-View Subspace Clustering with Prior Constraints”
Mehrnaz Najafi, Lifang He, and Philip S. Yu

DM661 “Few-Shot Partial Multi-Label Learning”
Yunfeng Zhao, Guoxian Yu, Lei Liu, Zhongmin Yan, Carlotta Domeniconi, and Lizhen Cui

DM663 “Nonlinear Causal Structure Learning for Mixed Data”
Wenjuan Wei and Lu Feng

DM673 “Cutting to the Chase with Warm-Start Contextual Bandits”
Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein

DM706 “Powered Hawkes-Dirichlet Process: Challenging Textual Clustering using a Flexible Temporal Prior”
Gaël Poux-Médard, Julien Velcin, and Sabine Loudcher

DM719 “Towards Interpretability and Personalization: A Predictive Framework for Clinical Time-series Analysis”
Yang Li, Xianli Zhang, Buyue Qian, Zeyu Gao, Chong Guan, Yefeng Zheng, Hansen Zheng, Fenglang Wu, and Chen Li

DM724 “Discriminative Additive Scale Loss for Deep Imbalanced Classification and Embedding”
Zhao Zhang, Weiming Jiang, Yang Wang, Qiaolin Ye, Mingbo Zhao, Mingliang Xu, and Meng Wang

DM752 “A Regularized Wasserstein Framework for Graph Kernels”
Asiri Wijesinghe, Qing Wang, and Stephen Gould

DM757 “Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records”
Shuai Niu, Qing Yin, Yunya SONG, Yike GUO, and Xian Yang

DM758 “Towards Generating Real-World Time Series Data”
Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, and Dongsheng Li

DM760 “PRGAN: Personalized Recommendation with Conditional Generative Adversarial Networks”
Jing Wen, Bi-Yi Chen, Chang-Dong Wang, and Zhihong Tian

DM762 “A Robust Algorithm to Unifying Offline Causal Inference and Online Multi-armed Bandit Learning”
Qiao Tang and Hong Xie

DM769 “TRIO:Task-agnostic dataset representation optimized for automatic algorithm selection”
Noy Cohen-Shapira and Lior Rokach

DM798 “Predictive Modeling of Clinical Events with Mutual Enhancement Between Longitudinal Patient Records and Medical Knowledge Graph”
Xiao Xu, Xian Xu, Yuyao Sun, Xiaoshuang Liu, Xiang Li, Guotong Xie, and Fei Wang

DM801 “DCF: An Efficient and Robust Density-Based Clustering Method”
Joshua Tobin and Mimi Zhang

DM813 “STAN: Adversarial Network for Cross-domain Question Difficulty Prediction”
Ye Huang, Wei Huang, Shiwei Tong, Qi Liu, Zhenya Huang, Enhong Chen, Jianhui Ma, Liang Wan, and Shijin Wang

DM817 “SCEHR: Supervised Contrastive Learning for Clinical Risk Predictions with Electronic Health Records”
Chengxi Zang and Fei Wang

DM828 “Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy”
Kunpeng Liu, Dongjie Wang, Pengfei Wang, Wan Du, Dapeng Oliver Wu, and Yanjie Fu

DM834 “Hypergraph Convolutional Network for Group Recommendation”
Renqi Jia, Xiaofei Zhou, Linhua Dong, and Shirui Pan

DM837 “MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta Learning”
Manqing Dong, Lina Yao, Xianzhi Wang, Xiwei Xu, and Liming Zhu

DM843 “PARWiS: Winner determination from Active Pairwise Comparisons under a Shoestring Budget”
Dev Sheth and Arun Rajkumar

DM847 “GNES: Learning to Explain Graph Neural Networks”
Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao

DM848 “Expert Knowledge-Guided Length-Variant Hierarchical Label Generation for Proposal Classification”
Meng Xiao, Ziyue Qiao, Yanjie Fu, Yi Du, Pengyang Wang, and Yuanchun Zhou

DM851 “Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval”
Dingrong Wang, Hitesh Sapkota, Xumin Liu, and Qi Yu

DM868 “MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems”
Yunyong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, and Sang-Wook Kim

DM872 “Risk-aware Temporal Cascade Reconstruction to Detect Asymptomatic Cases”
Hankyu Jang, Shreyas Pai, Bijaya Adhikari, and Sriram Pemmaraju

DM881 “Fast computation of distance-generalized cores using sampling”
Nikolaj Tatti

DM883 “USTEP: Unfixed Search Tree for Efficient Log Parsing”
Arthur Vervaet, Raja Chiky, and Mar Callau-Zori

DM886 “Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions”
Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, and Gautam Shroff

DM904 “Combining Ranking and Point-wise Losses for Training Deep Survival Analysis Models”
Lu Wang, Mark Chignell, and Yan Li

DM911 “Online Learning in Variable Feature Spaces with Mixed Data”
Yi He, Jiaxian Dong, Bo-Jian Hou, Yu Wang, and Fei Wang

DM915 “Precise Bayes Classifier: Summary of Results”
Amin Vahedian and Xun Zhou

DM921 “Topic-Noise Models: Modeling Topic and Noise Distributions in Social Media Post Collections”
Robert Churchill and Lisa Singh

DM936 “Gated Information Bottleneck for Generalization in Sequantial Environments”
Francesco Alesiani, Shujian Yu, and Xi Yu

DM938 “CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown Network”
Andrea Tonon and Fabio Vandin

DM942 “Deep Incremental RNN for Learning Sequential Data: A Lyapunov Stable Dynamical System”
Ziming Zhang, Guojun Wu, Yun Yue, Yanhua Li, and Xun Zhou

DM943 “THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting”
Geon Lee and Kijung Shin

DM947 “FGC-Stream: A novel joint miner for frequent generators and closed itemsets in data streams”
Louis-Romain Roux, Tomas Martin, and Petko Valtchev

DM972 “Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning”
Dongjie Wang, Kunpeng Liu, Pauline Johnson, Leilei Sun, Bowen Du, and Yanjie Fu

DM979 “Multi-way Time Series Join on Multi-length Patterns”
Md Parvez Mollah, Vinicius M. A. Souza, and Abdullah Mueen

DM980 “Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation”
Ruihong Qiu, Zi Huang, and Hongzhi Yin

DM986 “Climate Modeling with Neural Diffusion Equations”
Hwangyong Choi, Jeongwhan Choi, Jeehyun Hwang, and Noseong Park

DM987 “Hypergraph Ego-networks and Their Temporal Evolution”
Cazamere Comrie and Jon Kleinberg

DM988 “Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning”
Thai-Hoang Pham, Changchang Yin, Laxmi Mehta, Xueru Zhang, and Ping Zhang

DM995 “Global Convolutional Neural Processes”
Xuesong Wang, Lina Yao, Xianzhi Wang, Hye-young Paik, and Sen Wang

DM999 “Impression Allocation and Policy Search in Display Advertising”
di wu, cheng chen, xiujun chen, junwei pan, xun yang, qing tan, jian xu, and Kuang-Chih lee

DM1000 “FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance”
Ge Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, and Michael Sheng

DM1002 “Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting”
Sheoyon Jhin, Heejoo Shin, Seoyoung Hong, Solhee Park, and Noseong Park

DM1006 “SSDNet: State Space Decomposition Neural Network for Time Series Forecasting”
Yang Lin, Irena Koprinska, and Mashud Rana

DM1008 “Finding Age Path of Self-Paced Learning”
Zhou Zhai, Bin Gu, Li Xiang, and Heng Huang

DM1012 “Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-training”
Mingyue Cheng, Fajie Yuan, Liu Qi, Shenyang Ge, Xin Xin, and Chen Enhong

DM1027 “Conversion Prediction with Delayed Feedback: A Multi-task Learning Approach”
Yilin Hou, Guangming Zhao, Chuanren Liu, Zhonglin Zu, and Xiaoqiang Zhu

DM1031 “Temporal Clustering with External Memory Network for Disease Progression Modeling”
Zicong Zhang, Changchang Yin, and Ping Zhang

DM1032 “ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network”
Xingcheng Fu, Jianxin Li, Qingyun Sun, Cheng Ji, Jia Wu, Hao Peng, Senzhang Wang, Jiajun Tan, and Philip S. Yu

DM1055 “Group-Level Cognitive Diagnosis: A Multi-Task Learning Perspective”
Jie Huang, Liu Qi, Fei Wang, Zhenya Huang, Songtao Fang, Runze Wu, Chen Enhong, Yu Su, and Shijin Wang

DM1067 “Fair Decision-making Under Uncertainty”
Wenbin Zhang and Jeremy Weiss

DM1069 “Crowdsourcing with Self-paced Workers”
Xiangping Kang, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Wei Guo, Yazhou Ren, and Lizhen Cui

DM1082 “AutoEmb: Adaptive Embedding Dimension for Online Recommender Systems”
Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, and Xiwang Yang

DM1104 “Ultra fast warping window optimization for Dynamic Time Warping”
Chang Wei Tan, Matthieu Herrmann, and Geoffrey I. Webb

DM1148 “GANBLR: A Tabular Data Generation Model”
Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, and Gang Li

DM1155 “Fast Attributed Graph Embedding via Density of States”
Saurabh Sawlani, Lingxiao Zhao, and Leman Akoglu

DM1162 “Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural Network”
Liu Huijie, Wu Han, Zhang Le, Yu Runlong, Liu Ye, Liu Qi, and Chen Enhong

DM1168 “A Primal-Dual Multi-Instance SVM for Big Data Classifications”
Lodewijk Brand, Lauren Baker, Carla Ellefsen, Jackson Sargent, and Hua Wang

DM1197 “Preference-aware Group Task Assignment in Spatial Crowdsourcing: A Mutual Information-based Approach”
Yunchuan Li, Yan Zhao, and Kai Zheng

DM1200 “Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence”
Wennan Chang, Pengtao Dang, Changlin Wan, Xiaoyu Lu, Yue Fang, Tong Zhao, Yong Zang, Bo Li, Chi Zhang, and Sha Cao

DM1205 “Space Meets Time: Local Spacetime Neural Network For Traffic Flow Forecasting”
Song Yang, Jiamou Liu, and Kaiqi Zhao

DM1208 “Learning to Reweight Samples with Offline Loss Sequence”
Yuhua Wei, Chen Li, Xiaoyu Li, Jishang Wei, and Buyue Qian

 

Short Papers

DM214 “Dynamic Attributed Graph Prediction with Conditional Normalizing Flows”
Daheng Wang, Tong Zhao, Nitesh Chawla, and Meng Jiang

DM217 “Composition-Enhanced Graph Collaborative Filtering for Multi-behavior Recommendation”
Daqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Pengfei Wang, Minghua Deng, and Jinwen Ma

DM247 “Gaussian Process Model Learning for Time Series Classification”
Fabian Berns, Jan Huewel, and Christian Beecks

DM261 “Exploring the Long Short-Term Dependencies to Infer Shot Influence in Badminton Matches”
Wei-Yao Wang, Teng-Fong Chan, Hui-Kuo Yang, Chih-Chuan Wang, Yao-Chung Fan, and Wen-Chih Peng

DM290 “PaGAN: Generative Adversarial Network for Patent understanding”
Guillaume Guarino, Ahmed Samet, Amir Nafi, and Denis Cavallucci

DM291 “Generating Explanations for Recommendation Systems via Injective VAE”
ZeRui Cai and ZeFeng Cai

DM294 “Trajectory WaveNet: A Trajectory-Based Model for Traffic Forecasting”
Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku

DM298 “Self-supervised Universal Domain Adaptation with Adaptive Memory Separation”
Ronghang Zhu and Sheng Li

DM304 “HanBERT: A Hanzi-aware Pre-trained Language Model for Chinese Biomedical Text Mining”
Xiaosu Wang, Yun Xiong, Hao Niu, Jingwen Yue, Yangyong Zhu, and Philip S. Yu

DM330 “K-means for Evolving Data Streams”
Arkaitz Bidaurrazaga Barrueta, Aritz Perez, and Marco Capo

DM343 “Contrast Profile: A Novel Time Series Primitive that Allows Classification in Real World Settings”
Ryan Mercer, Sara Alaee, Alireza Abdoli, Shailendra Singh, Amy Murillo, and Eamonn Keogh

DM380 “Boosting Deep Ensemble Performance with Hierarchical Pruning”
Yanzhao Wu and Ling Liu

DM385 “Operation-level Progressive Differentiable Architecture Search”
Xunyu Zhu, Jian Li, Yong Liu, and Weiping Wang

DM390 “Fair Graph Auto-Encoder for Unbiased Graph Representations with Wasserstain Distance”
Wei Fan, Kunpeng Liu, Rui Xie, Hao Liu, Hui Xiong, and Yanjie Fu

DM396 “MERITS: Medication Recommendation for Chronic Disease with Irregular Time-Series”
Shuai Zhang, Jianxin Li, Haoyi Zhou, Qishan Zhu, Shanghang Zhang, and Danding Wang

DM399 “LIFE: Learning Individual FEatures for Multivariate Time Series Prediction with Missing Values”
Zhao-Yu Zhang, Shao-Qun Zhang, Yuan Jiang, and Zhi-Hua Zhou

DM408 “Spikelet: An Adaptive Symbolic Approximation for Finding Higher-Level Structure in Time Series”
Makoto Imamura and Takaaki Nakamura

DM418 “StarGAT: Star-Shaped Hierarchical Graph Attentional Network for Heterogeneous Network Representation Learning”
Wen-Zhi Li, Ling Huang, Chang-Dong Wang, and Yuxin Ye

DM423 “Gain-Some-Lose-Some: Reliable Quantification Under General Dataset Shift”
Benjamin Denham, Edmund Lai, Roopak Sinha, and M. Asif Naeem

DM437 “Density-Based Clustering for Adaptive Density Variation”
Li Qian, Claudia Plant, and Christian Böhm

DM447 “Limited-memory Common-directions Method With Subsampled Newton Directions for Large-scale Linear Classification”
Jui-Nan Yen and Chih-Jen Lin

DM450 “Aspect-based Sentiment Classification via Reinforcement Learning”
Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, and Yun Fu

DM457 “An Interpretable Ensemble of Naive Bayes Classifiers for Uncertain Categorical Data”
Marcelo Maia, Alexandre Plastino, and Alex Freitas

DM459 “Self-learn to Explain Siamese Networks Robustly”
Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, and Sihong Xie

DM463 “A Lookahead Algorithm for Robust Subspace Recovery”
Guihong Wan and Haim Schweitzer

DM465 “Online Testing of Subgroup Treatment Effects Based on Value Difference”
Miao Yu, Wenbin Lu, and Rui Song

DM473 “A new multiple instance algorithm using structural information”
Xiaoyan Zhu, Ting Wang, Jiayin Wang, Ying Xu, and Yuqian Liu

DM475 “STING: Self-attention based Time-series Imputation Networks using GAN”
Eunkyu Oh, Taehun Kim, Yunhu Ji, and Sushil Khyalia

DM487 “Improving Deep Forest by Exploiting High-order Interactions”
Yi-He Chen, Shen-Huan Lyu, and Yuan Jiang

DM509 “Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications”
BANG WU, Xiangwen Yang, Shirui Pan, and Xingliang Yuan

DM520 “Relation Network for Causal Reasoning Image Captioning”
Dongming Zhou and Jing Yang

DM521 “Pest-YOLO: Deep Image Mining and Multi-Feature Fusion for Real-Time Agriculture Pest Detection”
Zhe Tang, Zhengyun Chen, Fang Qi, Lingyan Zhang, and Shuhong Chen

DM543 “$C^3$-GAN: Complex-Condition-Controlled Urban Traffic Estimation through Generative Adversarial Networks”
Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, and Jun Luo

DM545 “Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference”
Shaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, and Junyu Dong

DM556 “Constrained Non-Affine Alignment of Embeddings”
Yuwei Wang, Yan Zheng, Yanqing Peng, Michael Yeh, Zhongfang Zhuang, Das Mahashweta, Bendre Mangesh, Feifei Li, Wei Zhang, and Jeff Phillips

DM577 “Bi-Level Attention Graph Neural Networks”
Roshni Iyer, Wei Wang, and Yizhou Sun

DM588 “SCALP – Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata”
Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin Rousseau, Yifan Peng, and Ying Ding

DM589 “Communication Efficient Tensor Factorization for Decentralized Healthcare Networks”
Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Joyce Ho, and Sivasubramanium Bhavani

DM601 “A general framework for mining concept-drifting data streams with evolvable features”
Jiaqi Peng, Jinxia Guo, Qinli Yang, Jianyun Lu, and Junming Shao

DM608 “Multimodal N-best List Rescoring with Weakly Supervised Pre-training in Hybrid Speech Recognition”
Yuanfeng Song, Xiaoling Huang, Xuefang Zhao, Di Jiang, and Raymond Chi-Wing Wong

DM611 “TEST-GCN: Topologically Enhanced Spatial-Temporal Graph Convolutional Networks for Traffic Forecasting”
Muhammad Afif Ali, Suriyanarayanan Venkatesan, Victor Liang, and Hannes Kruppa

DM624 “Alternative Ruleset Discovery to Support Black-box Model Predictions”
Yoichi Sasaki and Yuzuru Okajima

DM625 “Heterogeneous Stream-reservoir Graph Networks with Data Assimilation”
Shengyu Chen, Alison Appling, Samanth Oliver, Hayley Corson-Dosch, Jordan Read, Jeffrey Sadler, Jacob Zwart, and Xiaowei Jia

DM626 “Towards Stochastic Neural Network via Feature Distribution Calibration”
Hao Yang, Min Wang, Yun Zhou, and Yongxin Yang

DM630 “Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates”
Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Jonathan Weill, and Noam Koenigstein

DM634 “An Adversarial Framework of Higher-order and Local Features for Role-based Network Embedding”
Wang Zhang, Xuan Guo, Ting Pan, Lin Pan, Pengfei Jiao, and Wenjun Wang

DM637 “Adversarial Learning of Balanced Triangles for Accurate Community Detection on Signed Networks”
Yoonsuk Kang, Woncheol Lee, Yeon-Chang Lee, Kyungsik Han, and Sang-Wook Kim

DM638 “Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching”
Fan Zhou, Xiaocheng Tang, Chenfan Lu, Fan Zhang, Zhiwei Qin, Jieping Ye, and Hongtu Zhu

DM641 “Summarizing User-Item Matrix By Group Utility Maximization”
Yongjie Wang, Ke Wang, Cheng Long, and Chunyan Miao

DM650 “Adaptive Spatio-Temporal Convolutional Network for Traffic Prediction”
Mingyang Zhang, Yong Li, Funing Sun, Diansheng Guo, and Pan Hui

DM656 “Streaming Dynamic Graph Neural Networks for Continuous-Time Temporal Graph Modeling”
Sheng Tian, Tao Xiong, and Leilei Shi

DM695 “Jointly Multi-Similarity Loss for Deep Metric Learning”
Li Zhang, Shitian Shen, Lingxiao Li, and Han Wang

DM710 “Unified Fairness from Data to Learning Algorithm”
Yanfu Zhang, Lei Luo, and Heng Huang

DM722 “MetaEDL: Meta Evidential Learning For Uncertainty-Aware Cold-Start Recommendations”
Krishna Neupane, Ervine Zheng, and Qi Yu

DM733 “MC-RGCN: A Multi-Channel Recurrent Graph Convolutional Network to Learn High-Order Social Relations for Diffusion Prediction”
Ningbo Huang, Gang Zhou, Mengli Zhang, and Meng Zhang

DM743 “DIVINIA: Rare Object Localization and Search in Overhead Imagery”
Jonathan Amazon, Khurram Shafique, Zeeshan Rasheed, and Aaron Reite

DM776 “Federated Principal Component Analysis for Genome-Wide Association Studies”
Anne Hartebrodt, Reza Nasirigerdeh, David B. Blumenthal, and Richard Röttger

DM786 “Compressibility of Distributed Document Representations”
Blaž Škrlj and Matej Petković

DM792 “Promoting Fairness through Hyperparameter Optimization”
André Cruz, Pedro Saleiro, Catarina Belém, Carlos Soares, and Pedro Bizarro

DM802 “Accurately Quantifying under Score Variability”
André Maletzke, Denis dos Reis, Waqar Hassan, and Gustavo Batista

DM803 “Heterogeneous Graph Neural Network with Distance Encoding”
Houye Ji, Pan Li, Chuan Shi, and Cheng Yang

DM815 “Scalable Pareto Front Approximation for Deep Multi-Objective Learning”
Michael Ruchte and Josif Grabocka

DM818 “MCME: An Effective and Robust Framework for Modeling Correlations of Multiplex Network Embedding”
Pengfei Jiao, Ruili Lu, Di Jin, Yinghui Wang, and Huaming Wu

DM825 “Graph Neighborhood Routing and Random Walk for Session-based Recommendation”
Zizhuo Zhang and Bang Wang

DM829 “Thin Semantics Enhancement Guided by High-Frequency Priori Rule for Thin Structures Segmentation”
Yuting He, Rongjun Ge, Jiasong Wu, Jean-Louis Coatrieux, Huazhong Shu, Yang Chen, Guanyu Yang, and Shuo Li

DM831 “Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning”
Preethi Lahoti, Krishna Gummadi, and Gerhard Weikum

DM842 “Attacking Similarity-Based Sign Prediction”
Michał T. Godziszewski, Marcin Waniek, Yulin Zhu, Kai Zhou, Talal Rahwan, and Tomasz P. Michalak

DM854 “HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List Continuation”
Vijaikumar M, Deepesh Hada, and Shirish Shevade

DM869 “Out-of-Category Document Identification Using Target-Category Names as Weak Supervision”
Dongha Lee, Dongmin Hyun, Jiawei Han, and Hwanjo Yu

DM875 “SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series”
Jingwei Zuo, Karine Zeitouni, and Yehia Taher

DM878 “Adversarial Regularized Reconstruction for Anomaly Detection and Generation”
Angelica Liguori, Giuseppe Manco, Francesco Sergio Pisani, and Ettore Ritacco

DM889 “Exploring Reflective Limitation of Behavior Cloning in Autonomous Vehicles”
Mohammad Nazeri and Mahdi Bohlouli

DM934 “Causal Discovery with Flow-based Conditional Density Estimation”
Shaogang Ren, Haiyan Yin, Mingming Sun, and Ping Li

DM940 “PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields”
Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Long He, Naren Ramakrishnan, Danesh Tafti, and Anuj Karpatne

DM950 “A Multi-view Confidence-calibrated Framework for Fair and Stable Graph Representation Learning”
Xu Zhang, Liang Zhang, Bo Jin, and Xinjiang Lu

DM956 “ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding”
Wonjun Ko, Wonsik Jung, Eunjin Jeon, Ahmad Wisnu Mulyadi, and Heung-Il Suk

DM957 “Learnable Structural Semantic Readout for Graph Classification”
Dongha Lee, Su Kim, Seonghyeon Lee, Chanyoung Park, and Hwanjo Yu

DM959 “Semi-Supervised Graph Attention Networks for Event Representation Learning”
João Pedro Rodrigues Mattos and Ricardo Marcacini

DM964 “Learning Personal Human Biases and Representations for Subjective Tasks in Natural Language Processing”
Jan Kocoń, Marcin Gruza, Julita Bielaniewicz, Damian Grimling, Kamil Kanclerz, Piotr Miłkowski, and Przemysław Kazienko

DM971 “Personalized Compatibility Metric Learning”
Meet Taraviya, Anurag Beniwal, Yen-Liang Lin, and Larry Davis

DM976 “Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone”
Hui Guan, Umang Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, and Xipeng Shen

DM994 “Practitioner-Centric Approach for Early Incident Detection Using Crowdsourced Data for Emergency Services”
Yasas Senarath, Ayan Mukhopadhyay, Sayyed Mohsen Vazirizade, Hemant Purohit, Saideep Nannapaneni, and Abhishek Dubey

DM1003 “PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series”
Futoon M. Abushaqra, Hao Xue, Yongli Ren, and Flora D. Salim

DM1007 “Detecting Adversaries in Crowdsourcing”
Panagiotis Traganitis and Georgios B. Giannakis

DM1015 “Learning Dynamic User Interactions for Online Forum Commenting Prediction”
Wu-Jiu Sun, Xiao Fan Liu, and Fei Shen

DM1023 “DhakaNet: Unstructured Vehicle Detection using Limited Computational Resources”
Tarik Reza Toha, Masfiqur Rahaman, Saiful Islam Salim, Mainul Hossain, Arif Mohamin Sadri, and A. B. M. Alim Al Islam

DM1044 “Overfitting Avoidance in Tensor Train Factorization and Completion: Prior Analysis and Inference”
Le Xu, Cheng Lei, Ngai Wong, and Yik-Chung Wu

DM1049 “Addressing Exposure Bias in Uplift Modeling for Large-scale Online Advertising”
Wenwei Ke, Chuanren Liu, Xiangfu Shi, Yiqiao Dai, Philip Yu, and Xiaoqiang Zhu

DM1099 “GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs”
Yucai Fan, Yuhang Yao, and Carlee Joe-Wong

DM1103 “Multi Classification prediction of Alzheimer’s disease based on fusing multi-modal features”
Qiao Pan, Ke Ding, and Dehua Chen

DM1105 “Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase Generation”
Cangqi Zhou, Jinling Shang, Jing Zhang, Qianmu Li, and Dianming Hu

DM1113 “AdaBoosting Clusters on Graph Neural Networks”
Li Zheng, Jun Gao, Zhao Li, and Ji Zhang

DM1123 “GQNAS: Graph Q Network for Neural Architecture Search”
Yijian Qin, Xin Wang, Peng Cui, and Wenwu Zhu

DM1125 “TCube: Domain-Agnostic Neural Time-series Narration”
Mandar Sharma, John Brownstein, and Naren Ramakrishnan

DM1150 “Heterogeneous Graph Neural Architecture Search”
Yang Gao, Peng Zhang, Zhao Li, Chuan Zhou, Hong Yang, Yongchao Liu, and Yue Hu

DM1154 “Incomplete Multi-view Multi-label Active Learning”
Chuanwei Qu, Kuangmeng Wang, Hong Zhang, Guoxian Yu, and Carlotta Domeniconi

DM1167 “Source Inference Attacks in Federated Learning”
Hongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, and Xuyun Zhang

DM1179 “Zero-shot Key Information Extraction from Mixed-Style Tables: Pre-training on Wikipedia”
Yingpeng Hu, Qingping Yang, Rongyu Cao, Hongwei Li, and Ping Luo

DM1183 “Robust BiPoly-Matching for Multi-Granular Entities”
Ween Jiann Lee, Maksim Tkachenko, and Hady Lauw