- Krzysztof Rudas, Szymon Jaroszewicz:
Regularization for Uplift Regression. ECML/PKDD (1) 2023: 593-608 - Anastasiia Sedova, Lena Zellinger, Benjamin Roth:
Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal. ECML/PKDD (1) 2023: 237-253 - Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu:
PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework. ECML/PKDD (1) 2023: 559-575 - Rishabh Upadhyay, Gabriella Pasi, Marco Viviani:
A Passage Retrieval Transformer-Based Re-Ranking Model for Truthful Consumer Health Search. ECML/PKDD (1) 2023: 355-371 - Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer:
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. ECML/PKDD (1) 2023: 459-474 - Mike Wong, Edward Raff, James Holt, Ravi Netravali:
Marvolo: Programmatic Data Augmentation for Deep Malware Detection. ECML/PKDD (1) 2023: 270-285 - Bowen Xing, Ivor W. Tsang:
Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. ECML/PKDD (1) 2023: 305-322 - Yuting Yang, Pei Huang, Juan Cao, Feifei Ma, Jian Zhang, Jintao Li:
Quantifying Robustness to Adversarial Word Substitutions. ECML/PKDD (1) 2023: 95-112 - Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) 2023: 254-269 - Jingrui Zhang, Ninh Pham, Gillian Dobbie:
A Transductive Forest for Anomaly Detection with Few Labels. ECML/PKDD (1) 2023: 286-301 - Mingyu Zhao, Weidong Yang, Feiping Nie:
Transformer-Based Contrastive Multi-view Clustering via Ensembles. ECML/PKDD (1) 2023: 678-694 - Yimei Zheng, Caiyan Jia, Jian Yu:
Contrastive Learning with Cluster-Preserving Augmentation for Attributed Graph Clustering. ECML/PKDD (1) 2023: 644-661 - Zhiyu Zhu, Jiayu Zhang, Zhibo Jin, Xinyi Wang, Minhui Xue, Jun Shen, Kim-Kwang Raymond Choo, Huaming Chen:
Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning. ECML/PKDD (1) 2023: 147-163 - Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja:
Contrastive Hierarchical Clustering. ECML/PKDD (1) 2023: 627-643 - Danai Koutra, Claudia Plant, Manuel Gomez-Rodriguez, Elena Baralis, Francesco Bonchi:
Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part I. Lecture Notes in Computer Science 14169, Springer 2023, ISBN 978-3-031-43411-2 [contents]