- Victor Agostinelli, Lizhong Chen:
Improving Autoregressive NLP Tasks via Modular Linearized Attention. ECML/PKDD (4) 2023: 90-106 - Abdullah Alchihabi, Yuhong Guo:
GDM: Dual Mixup for Graph Classification with Limited Supervision. ECML/PKDD (3) 2023: 309-324 - Giambattista Amati, Antonio Cruciani, Daniele Pasquini, Paola Vocca, Simone Angelini:
propagate: A Seed Propagation Framework to Compute Distance-Based Metrics on Very Large Graphs. ECML/PKDD (3) 2023: 671-688 - Srinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith:
Continuous Depth Recurrent Neural Differential Equations. ECML/PKDD (2) 2023: 223-238 - Jiaqi Bai, Zhao Yan, Ze Yang, Jian Yang, Xinnian Liang, Hongcheng Guo, Zhoujun Li:
KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation. ECML/PKDD (2) 2023: 525-542 - Tim Bakker, Herke van Hoof, Max Welling:
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. ECML/PKDD (1) 2023: 3-19 - Arn Baudzus, Bin Li, Adnane Jadid, Emmanuel Müller:
The Good, The Bad, and The Average: Benchmarking of Reconstruction Based Multivariate Time Series Anomaly Detection. ECML/PKDD (7) 2023: 356-360 - Amanda Bertschinger, Q. Tyrell Davis, James P. Bagrow, Josh C. Bongard:
The Metric is the Message: Benchmarking Challenges for Neural Symbolic Regression. ECML/PKDD (4) 2023: 161-177 - Milan Bhan, Jean-Noël Vittaut, Nicolas Chesneau, Marie-Jeanne Lesot:
TIGTEC: Token Importance Guided TExt Counterfactuals. ECML/PKDD (3) 2023: 496-512 - Asmita Bhat, Nooshin HajiGhassemi, Deepak Nagaraj, Sophie Fellenz:
Constraint-Based Parameterization and Disentanglement of Aerodynamic Shapes Using Deep Generative Models. ECML/PKDD (6) 2023: 360-376 - Manuele Bicego, Ferdinando Cicalese:
On the Good Behaviour of Extremely Randomized Trees in Random Forest-Distance Computation. ECML/PKDD (4) 2023: 645-660 - Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban:
Is My Neural Net Driven by the MDL Principle? ECML/PKDD (2) 2023: 173-189 - Mirko Bunse, Lukas Pfahler:
Class-Conditional Label Noise in Astroparticle Physics. ECML/PKDD (6) 2023: 19-35 - Yuzhou Chen, Tian Jiang, Yulia R. Gel:
H2-Nets: Hyper-hodge Convolutional Neural Networks for Time-Series Forecasting. ECML/PKDD (5) 2023: 271-289 - Hongjiang Chen, Pengfei Jiao, Huijun Tang, Huaming Wu:
Temporal Graph Representation Learning with Adaptive Augmentation Contrastive. ECML/PKDD (2) 2023: 683-699 - Ying Chen, Rui Liu, Zhihui Li, Andy Song:
F-3DNet: Leveraging Inner Order of Point Clouds for 3D Object Detection. ECML/PKDD (6) 2023: 346-359 - Jiayao Chen, Rui Wang, Jueying He, Mark Junjie Li:
Encouraging Sparsity in Neural Topic Modeling with Non-Mean-Field Inference. ECML/PKDD (4) 2023: 142-158 - Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du:
Real: A Representative Error-Driven Approach for Active Learning. ECML/PKDD (1) 2023: 20-37 - Haotian Chen, Han Zhang, Houjing Guo, Shuchang Yi, Bingsheng Chen, Xiangdong Zhou:
SALAS: Supervised Aspect Learning Improves Abstractive Multi-document Summarization Through Aspect Information Loss. ECML/PKDD (4) 2023: 55-70 - Wenkai Chen, Chuang Zhu, Mengting Li:
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels. ECML/PKDD (2) 2023: 3-19 - Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Thuc Duy Le, Jixue Liu:
Learning Conditional Instrumental Variable Representation for Causal Effect Estimation. ECML/PKDD (1) 2023: 525-540 - Guixiang Cheng, Xin Yan, Shengxiang Gao, Guangyi Xu, Xianghua Miao:
CasSampling: Exploring Efficient Cascade Graph Learning for Popularity Prediction. ECML/PKDD (3) 2023: 70-86 - Jiho Choi, Junghoon Park, Woocheol Kim, Jin-Hyeok Park, Yumin Suh, Minchang Sung:
PU GNN: Chargeback Fraud Detection in P2E MMORPGs via Graph Attention Networks with Imbalanced PU Labels. ECML/PKDD (6) 2023: 243-258 - Jyotishka Ray Choudhury, Aytijhya Saha, Sarbojit Roy, Subhajit Dutta:
Robust Classification of High-Dimensional Data Using Data-Adaptive Energy Distance. ECML/PKDD (5) 2023: 86-101 - Priyanka Chudasama, Tushar Kadam, Rajat Patel, Aakarsh Malhotra, Manoj Magam:
Contrastive Representation Through Angle and Distance Based Loss for Partial Label Learning. ECML/PKDD (4) 2023: 677-692 - Gabriele Ciravegna, Frédéric Precioso, Alessandro Betti, Kevin Mottin, Marco Gori:
Knowledge-Driven Active Learning. ECML/PKDD (1) 2023: 38-54 - Jie Dai, Xuguang Chen:
On the Distributional Convergence of Temporal Difference Learning. ECML/PKDD (4) 2023: 439-454 - Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann:
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. ECML/PKDD (3) 2023: 479-495 - Cássio Fraga Dantas, Thalita F. Drumond, Diego Marcos, Dino Ienco:
Counterfactual Explanations for Remote Sensing Time Series Data: An Application to Land Cover Classification. ECML/PKDD (7) 2023: 20-36 - Arpan Dasgupta, Pawan Kumar:
Alpha Elimination: Using Deep Reinforcement Learning to Reduce Fill-In During Sparse Matrix Decomposition. ECML/PKDD (4) 2023: 472-488