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ORCIDPKDD / ECML 2024: Vilnius, Lithuania - Part III
- Albert Bifet
, Jesse Davis, Tomas Krilavicius, Meelis Kull, Eirini Ntoutsi, Indre Zliobaite:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14943, Springer 2024, ISBN 978-3-031-70351-5
Research Track
- Jingxuan Wei, Cheng Tan, Zhangyang Gao, Linzhuang Sun, Bihui Yu, Ruifeng Guo, Stan Z. Li:
Interpretable and Generalizable Spatiotemporal Predictive Learning with Disentangled Consistency. 3-20 - Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann:
Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency. 21-38 - Yuhui Li, Zejia Wu, Chao Zhang, Hongyang Zhang:
Direct-Effect Risk Minimization for Domain Generalization. 39-57 - Ali Dadras, Sourasekhar Banerjee, Karthik Prakhya, Alp Yurtsever:
Federated Frank-Wolfe Algorithm. 58-75 - Yunhui Liu, Huaisong Zhang, Tieke He, Tao Zheng, Jianhua Zhao:
Bootstrap Latents of Nodes and Neighbors for Graph Self-supervised Learning. 76-92 - Tamim El Ahmad, Junjie Yang, Pierre Laforgue, Florence d'Alché-Buc:
Deep Sketched Output Kernel Regression for Structured Prediction. 93-110 - Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii, Alexander Kravberg, Petra Poklukar, Anastasia Varava, Danica Kragic:
Hyperbolic Delaunay Geometric Alignment. 111-126 - Haitao Wang, Hejun Wu:
ApmNet: Toward Generalizable Visual Continuous Control with Pre-trained Image Models. 127-142 - Pengxiang Wang, Hongbo Bo, Jun Hong, Weiru Liu, Kedian Mu:
AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental Learning. 143-160 - Soroush Ghandi, Benjamin Quost, Cassio de Campos:
Probabilistic Circuits with Constraints via Convex Optimization. 161-177 - Chutian Jiang, Hansong Zhou, Xiaonan Zhang, Shayok Chakraborty:
FedAR: Addressing Client Unavailability in Federated Learning with Local Update Approximation and Rectification. 178-196 - Yongchao Wu, Aron Henriksson:
Selecting from Multiple Strategies Improves the Foreseeable Reasoning of Tool-Augmented Large Language Models. 197-212 - Sahara Ali, Omar Faruque, Jianwu Wang:
Estimating Direct and Indirect Causal Effects of Spatiotemporal Interventions in Presence of Spatial Interference. 213-230 - Jiaxu Liu, Xinping Yi, Sihao Wu, Xiangyu Yin, Tianle Zhang, Xiaowei Huang, Shi Jin:
Continuous Geometry-Aware Graph Diffusion via Hyperbolic Neural PDE. 231-249 - Xizhi Gu, Hongzheng Li, Shihong Gao, Xinyan Zhang, Lei Chen, Yingxia Shao:
SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training. 250-266 - Qing En, Yuhong Guo:
AKGNet: Attribute Knowledge Guided Unsupervised Lung-Infected Area Segmentation. 267-283 - Jiashu Han, Shanshan Feng, Min Zhou, Xinyu Zhang, Yew Soon Ong, Xutao Li:
Diffusion Model in Normal Gathering Latent Space for Time Series Anomaly Detection. 284-300 - Rikuto Yamazono, Hirotake Hachiya:
Permutation Dependent Feature Mixing for Multivariate Time Series Forecasting. 301-316 - Jiayi Li, Ruilin Luo, Jiaqi Sun, Jing Xiao, Yujiu Yang:
Prior Bilinear-Based Models for Knowledge Graph Completion. 317-334 - Siyu Wang, Shengran Dai, Jianhui Jiang:
Thinking Like an Author: A Zero-Shot Learning Approach to Keyphrase Generation with Large Language Model. 335-350 - Chengyu Yao, Hong Huang, Hang Gao, Fengge Wu, Haiming Chen, Junsuo Zhao:
Molecular Graph Representation Learning via Structural Similarity Information. 351-367 - Xiu Susie Fang, Xinyang Du, Hao Chen, Ziqi Wei, Yong Zhan, Guohao Sun:
Efficient Privacy-Preserving Truth Discovery and Copy Detection in Crowdsourcing. 368-385 - Lingfu Wang, Zuobin Xiong, Guangchun Luo, Wei Li, Aiguo Chen:
FCFL: A Fairness Compensation-Based Federated Learning Scheme with Accumulated Queues. 386-402 - Xiaosheng Li, Yifan Wu, Wei Jiang, Ying Li, Jianguo Li:
MMDL-Based Data Augmentation with Domain Knowledge for Time Series Classification. 403-420 - Sandra Gilhuber, Anna Beer, Yunpu Ma, Thomas Seidl:
FALCUN: A Simple and Efficient Deep Active Learning Strategy. 421-439 - Cássio F. Dantas, Raffaele Gaetano, Dino Ienco:
Semi-supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-labelling. 440-456
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