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ORCIDPKDD / ECML 2024: Vilnius, Lithuania - Part I
- 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 I. Lecture Notes in Computer Science 14941, Springer 2024, ISBN 978-3-031-70340-9
Research Track
- Zahra Atashgahi, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu:
Adaptive Sparsity Level During Training for Efficient Time Series Forecasting with Transformers. 3-20 - Haowei Xu, Chao Gao, Xianghua Li, Zhen Wang:
RumorMixer: Exploring Echo Chamber Effect and Platform Heterogeneity for Rumor Detection. 21-37 - Amihossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning. 38-55 - Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, Markus Schedl:
Modular Debiasing of Latent User Representations in Prototype-Based Recommender Systems. 56-72 - Xiliang Yang, Shenyang Deng, Shicong Liu, Yuanchi Suo, Wing W. Y. Ng, Jianjun Zhang:
A Mathematics Framework of Artificial Shifted Population Risk and Its Further Understanding Related to Consistency Regularization. 73-88 - Fabian Stermann, Ilias Chalkidis, Amihossein Vahidi, Bernd Bischl, Mina Rezaei:
Attention-Driven Dropout: A Simple Method to Improve Self-supervised Contrastive Sentence Embeddings. 89-106 - Ao Zhou, Bin Liu, Jin Wang, Kaiwei Sun, Kelin Liu:
AEMLO: AutoEncoder-Guided Multi-label Oversampling. 107-124 - Antonio Cruciani:
MANTRA: Temporal Betweenness Centrality Approximation Through Sampling. 125-143 - Kazuki Uematsu, Kosuke Haruki, Taiji Suzuki, Mitsuhiro Kimura, Takahiro Takimoto, Hideyuki Nakagawa:
Dimensionality-Induced Information Loss of Outliers in Deep Neural Networks. 144-160 - Wujiang Xu, Xuying Ning, Wenfang Lin, Mingming Ha, Qiongxu Ma, Qianqiao Liang, Xuewen Tao, Linxun Chen, Bing Han, Minnan Luo:
Towards Open-World Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach. 161-179 - Eshant English, Matthias Kirchler, Christoph Lippert:
MixerFlow: MLP-Mixer Meets Normalising Flows. 180-196 - Tuan-Anh Nguyen, Kim Thang Nguyen, Denis Trystram:
Handling Delayed Feedback in Distributed Online Optimization: A Projection-Free Approach. 197-211 - Dashan Gao, Canhui Wu, Xiaojin Zhang, Xin Yao, Qiang Yang:
Secure Dataset Condensation for Privacy-Preserving and Efficient Vertical Federated Learning. 212-229 - Giacomo Turri, Luca Romeo:
Neighborhood Component Feature Selection for Multiple Instance Learning Paradigm. 230-247 - Pengnian Qi, Zhiyuan Zha, Biao Qin:
MESS: Coarse-Grained Modular Two-Way Dialogue Entity Linking Framework. 248-263 - Tingting Dai, Qiao Liu, Yang Xie, Yue Zeng, Rui Hou, Yanglei Gan:
Session Target Pair: User Intent Perceiving Networks for Session-Based Recommendation. 264-278 - Yuting Liu, Liu Yang, Yu Wang:
Hierarchical Fine-Grained Visual Classification Leveraging Consistent Hierarchical Knowledge. 279-295 - Xukun Zhou, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Muqiao Yang, Jun He:
Backdoor Attacks with Input-Unique Triggers in NLP. 296-312 - Dashan Gao, Sheng Wan, Hanlin Gu, Lixin Fan, Xin Yao, Qiang Yang:
Label Privacy Source Coding in Vertical Federated Learning. 313-331 - Auday Berro, Boualem Benatallah, Yacine Gaci, Khalid Benabdeslem:
Error Types in Transformer-Based Paraphrasing Models: A Taxonomy, Paraphrase Annotation Model and Dataset. 332-349 - Hongyu Zhang, Dongyi Zheng, Lin Zhong, Xu Yang, Jiyuan Feng, Yunqing Feng, Qing Liao:
FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling. 350-366 - Alessio Cascione, Mattia Setzu, Riccardo Guidotti:
Data-Agnostic Pivotal Instances Selection for Decision-Making Models. 367-386 - Lijing Zheng, Jihong Wang, Huan Liu, Minnan Luo:
Disentangled Counterfactual Graph Augmentation Framework for Fair Graph Learning with Information Bottleneck. 387-405 - Anis Fradi, Chafik Samir:
A New Framework for Evaluating the Validity and the Performance of Binary Decisions on Manifold-Valued Data. 406-421 - Kostadin Cvejoski, Ramsés J. Sánchez, César Ojeda:
The Future is Different: Predicting Reddits Popularity with Variational Dynamic Language Models. 422-439 - Rahul Mehta, Bhavyajeet Singh, Vasudeva Varma, Manish Gupta:
CircuitVQA: A Visual Question Answering Dataset for Electrical Circuit Images. 440-460
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