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